Analysis of Variance: A statistical technique that isolates and assesses the contributions of categorical independent variables to variation in the mean of a continuous dependent variable.Models, Genetic: Theoretical representations that simulate the behavior or activity of genetic processes or phenomena. They include the use of mathematical equations, computers, and other electronic equipment.Genetic Variation: Genotypic differences observed among individuals in a population.Breeding: The production of offspring by selective mating or HYBRIDIZATION, GENETIC in animals or plants.Quantitative Trait, Heritable: A characteristic showing quantitative inheritance such as SKIN PIGMENTATION in humans. (From A Dictionary of Genetics, 4th ed)Models, Statistical: Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.Reproducibility of Results: The statistical reproducibility of measurements (often in a clinical context), including the testing of instrumentation or techniques to obtain reproducible results. The concept includes reproducibility of physiological measurements, which may be used to develop rules to assess probability or prognosis, or response to a stimulus; reproducibility of occurrence of a condition; and reproducibility of experimental results.Regression Analysis: Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable.Quantitative Trait Loci: Genetic loci associated with a QUANTITATIVE TRAIT.Phenotype: The outward appearance of the individual. It is the product of interactions between genes, and between the GENOTYPE and the environment.Environment: The external elements and conditions which surround, influence, and affect the life and development of an organism or population.Linear Models: Statistical models in which the value of a parameter for a given value of a factor is assumed to be equal to a + bx, where a and b are constants. The models predict a linear regression.Twins, Dizygotic: Two offspring from the same PREGNANCY. They are from two OVA, fertilized at about the same time by two SPERMATOZOA. Such twins are genetically distinct and can be of different sexes.Computer Simulation: Computer-based representation of physical systems and phenomena such as chemical processes.Twins, Monozygotic: Two off-spring from the same PREGNANCY. They are from a single fertilized OVUM that split into two EMBRYOS. Such twins are usually genetically identical and of the same sex.Likelihood Functions: Functions constructed from a statistical model and a set of observed data which give the probability of that data for various values of the unknown model parameters. Those parameter values that maximize the probability are the maximum likelihood estimates of the parameters.Algorithms: A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.Data Interpretation, Statistical: Application of statistical procedures to analyze specific observed or assumed facts from a particular study.Genotype: The genetic constitution of the individual, comprising the ALLELES present at each GENETIC LOCUS.Selection, Genetic: Differential and non-random reproduction of different genotypes, operating to alter the gene frequencies within a population.Genetics, Population: The discipline studying genetic composition of populations and effects of factors such as GENETIC SELECTION, population size, MUTATION, migration, and GENETIC DRIFT on the frequencies of various GENOTYPES and PHENOTYPES using a variety of GENETIC TECHNIQUES.Factor Analysis, Statistical: A set of statistical methods for analyzing the correlations among several variables in order to estimate the number of fundamental dimensions that underlie the observed data and to describe and measure those dimensions. It is used frequently in the development of scoring systems for rating scales and questionnaires.Inheritance Patterns: The different ways GENES and their ALLELES interact during the transmission of genetic traits that effect the outcome of GENE EXPRESSION.Inbreeding: The mating of plants or non-human animals which are closely related genetically.Time Factors: Elements of limited time intervals, contributing to particular results or situations.Questionnaires: Predetermined sets of questions used to collect data - clinical data, social status, occupational group, etc. The term is often applied to a self-completed survey instrument.Principal Component Analysis: Mathematical procedure that transforms a number of possibly correlated variables into a smaller number of uncorrelated variables called principal components.Bayes Theorem: A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result.Monte Carlo Method: In statistics, a technique for numerically approximating the solution of a mathematical problem by studying the distribution of some random variable, often generated by a computer. The name alludes to the randomness characteristic of the games of chance played at the gambling casinos in Monte Carlo. (From Random House Unabridged Dictionary, 2d ed, 1993)Statistics as Topic: The science and art of collecting, summarizing, and analyzing data that are subject to random variation. The term is also applied to the data themselves and to the summarization of the data.Crosses, Genetic: Deliberate breeding of two different individuals that results in offspring that carry part of the genetic material of each parent. The parent organisms must be genetically compatible and may be from different varieties or closely related species.Models, Biological: Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment.Genetic Markers: A phenotypically recognizable genetic trait which can be used to identify a genetic locus, a linkage group, or a recombination event.Twins: Two individuals derived from two FETUSES that were fertilized at or about the same time, developed in the UTERUS simultaneously, and born to the same mother. Twins are either monozygotic (TWINS, MONOZYGOTIC) or dizygotic (TWINS, DIZYGOTIC).Body Weight: The mass or quantity of heaviness of an individual. It is expressed by units of pounds or kilograms.Epistasis, Genetic: A form of gene interaction whereby the expression of one gene interferes with or masks the expression of a different gene or genes. Genes whose expression interferes with or masks the effects of other genes are said to be epistatic to the effected genes. Genes whose expression is affected (blocked or masked) are hypostatic to the interfering genes.Genetic Linkage: The co-inheritance of two or more non-allelic GENES due to their being located more or less closely on the same CHROMOSOME.Alleles: Variant forms of the same gene, occupying the same locus on homologous CHROMOSOMES, and governing the variants in production of the same gene product.Sample Size: The number of units (persons, animals, patients, specified circumstances, etc.) in a population to be studied. The sample size should be big enough to have a high likelihood of detecting a true difference between two groups. (From Wassertheil-Smoller, Biostatistics and Epidemiology, 1990, p95)Chromosome Mapping: Any method used for determining the location of and relative distances between genes on a chromosome.Psychometrics: Assessment of psychological variables by the application of mathematical procedures.Sex Factors: Maleness or femaleness as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or effect of a circumstance. It is used with human or animal concepts but should be differentiated from SEX CHARACTERISTICS, anatomical or physiological manifestations of sex, and from SEX DISTRIBUTION, the number of males and females in given circumstances.Cross-Sectional Studies: Studies in which the presence or absence of disease or other health-related variables are determined in each member of the study population or in a representative sample at one particular time. This contrasts with LONGITUDINAL STUDIES which are followed over a period of time.Diseases in Twins: Disorders affecting TWINS, one or both, at any age.Age Factors: Age as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or the effect of a circumstance. It is used with human or animal concepts but should be differentiated from AGING, a physiological process, and TIME FACTORS which refers only to the passage of time.Weaning: Permanent deprivation of breast milk and commencement of nourishment with other food. (From Stedman, 25th ed)Cattle: Domesticated bovine animals of the genus Bos, usually kept on a farm or ranch and used for the production of meat or dairy products or for heavy labor.Polymorphism, Single Nucleotide: A single nucleotide variation in a genetic sequence that occurs at appreciable frequency in the population.Biometry: The use of statistical and mathematical methods to analyze biological observations and phenomena.Reference Values: The range or frequency distribution of a measurement in a population (of organisms, organs or things) that has not been selected for the presence of disease or abnormality.Sex Characteristics: Those characteristics that distinguish one SEX from the other. The primary sex characteristics are the OVARIES and TESTES and their related hormones. Secondary sex characteristics are those which are masculine or feminine but not directly related to reproduction.Multifactorial Inheritance: A phenotypic outcome (physical characteristic or disease predisposition) that is determined by more than one gene. Polygenic refers to those determined by many genes, while oligogenic refers to those determined by a few genes.Gene Frequency: The proportion of one particular in the total of all ALLELES for one genetic locus in a breeding POPULATION.Gene-Environment Interaction: The combined effects of genotypes and environmental factors together on phenotypic characteristics.Longitudinal Studies: Studies in which variables relating to an individual or group of individuals are assessed over a period of time.Aging: The gradual irreversible changes in structure and function of an organism that occur as a result of the passage of time.Image Processing, Computer-Assisted: A technique of inputting two-dimensional images into a computer and then enhancing or analyzing the imagery into a form that is more useful to the human observer.Models, Theoretical: Theoretical representations that simulate the behavior or activity of systems, processes, or phenomena. They include the use of mathematical equations, computers, and other electronic equipment.Sensitivity and Specificity: Binary classification measures to assess test results. Sensitivity or recall rate is the proportion of true positives. Specificity is the probability of correctly determining the absence of a condition. (From Last, Dictionary of Epidemiology, 2d ed)Observer Variation: The failure by the observer to measure or identify a phenomenon accurately, which results in an error. Sources for this may be due to the observer's missing an abnormality, or to faulty technique resulting in incorrect test measurement, or to misinterpretation of the data. Two varieties are inter-observer variation (the amount observers vary from one another when reporting on the same material) and intra-observer variation (the amount one observer varies between observations when reporting more than once on the same material).Genome-Wide Association Study: An analysis comparing the allele frequencies of all available (or a whole GENOME representative set of) polymorphic markers in unrelated patients with a specific symptom or disease condition, and those of healthy controls to identify markers associated with a specific disease or condition.Twin Studies as Topic: Methods of detecting genetic etiology in human traits. The basic premise of twin studies is that monozygotic twins, being formed by the division of a single fertilized ovum, carry identical genes, while dizygotic twins, being formed by the fertilization of two ova by two different spermatozoa, are genetically no more similar than two siblings born after separate pregnancies. (Last, J.M., A Dictionary of Epidemiology, 2d ed)Mathematics: The deductive study of shape, quantity, and dependence. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 6th ed)Least-Squares Analysis: A principle of estimation in which the estimates of a set of parameters in a statistical model are those quantities minimizing the sum of squared differences between the observed values of a dependent variable and the values predicted by the model.Probability: The study of chance processes or the relative frequency characterizing a chance process.Bias (Epidemiology): Any deviation of results or inferences from the truth, or processes leading to such deviation. Bias can result from several sources: one-sided or systematic variations in measurement from the true value (systematic error); flaws in study design; deviation of inferences, interpretations, or analyses based on flawed data or data collection; etc. There is no sense of prejudice or subjectivity implied in the assessment of bias under these conditions.Mathematical Computing: Computer-assisted interpretation and analysis of various mathematical functions related to a particular problem.Neuropsychological Tests: Tests designed to assess neurological function associated with certain behaviors. They are used in diagnosing brain dysfunction or damage and central nervous system disorders or injury.Magnetic Resonance Imaging: Non-invasive method of demonstrating internal anatomy based on the principle that atomic nuclei in a strong magnetic field absorb pulses of radiofrequency energy and emit them as radiowaves which can be reconstructed into computerized images. The concept includes proton spin tomographic techniques.Microsatellite Repeats: A variety of simple repeat sequences that are distributed throughout the GENOME. They are characterized by a short repeat unit of 2-8 basepairs that is repeated up to 100 times. They are also known as short tandem repeats (STRs).Biomechanical Phenomena: The properties, processes, and behavior of biological systems under the action of mechanical forces.Risk Factors: An aspect of personal behavior or lifestyle, environmental exposure, or inborn or inherited characteristic, which, on the basis of epidemiologic evidence, is known to be associated with a health-related condition considered important to prevent.Cohort Studies: Studies in which subsets of a defined population are identified. These groups may or may not be exposed to factors hypothesized to influence the probability of the occurrence of a particular disease or other outcome. Cohorts are defined populations which, as a whole, are followed in an attempt to determine distinguishing subgroup characteristics.Biological Evolution: The process of cumulative change over successive generations through which organisms acquire their distinguishing morphological and physiological characteristics.Severity of Illness Index: Levels within a diagnostic group which are established by various measurement criteria applied to the seriousness of a patient's disorder.Genetic Heterogeneity: The presence of apparently similar characters for which the genetic evidence indicates that different genes or different genetic mechanisms are involved in different pedigrees. In clinical settings genetic heterogeneity refers to the presence of a variety of genetic defects which cause the same disease, often due to mutations at different loci on the same gene, a finding common to many human diseases including ALZHEIMER DISEASE; CYSTIC FIBROSIS; LIPOPROTEIN LIPASE DEFICIENCY, FAMILIAL; and POLYCYSTIC KIDNEY DISEASES. (Rieger, et al., Glossary of Genetics: Classical and Molecular, 5th ed; Segen, Dictionary of Modern Medicine, 1992)Stochastic Processes: Processes that incorporate some element of randomness, used particularly to refer to a time series of random variables.Reproduction: The total process by which organisms produce offspring. (Stedman, 25th ed)Multivariate Analysis: A set of techniques used when variation in several variables has to be studied simultaneously. In statistics, multivariate analysis is interpreted as any analytic method that allows simultaneous study of two or more dependent variables.Genetic Predisposition to Disease: A latent susceptibility to disease at the genetic level, which may be activated under certain conditions.Animals, Domestic: Animals which have become adapted through breeding in captivity to a life intimately associated with humans. They include animals domesticated by humans to live and breed in a tame condition on farms or ranches for economic reasons, including LIVESTOCK (specifically CATTLE; SHEEP; HORSES; etc.), POULTRY; and those raised or kept for pleasure and companionship, e.g., PETS; or specifically DOGS; CATS; etc.Genetic Pleiotropy: A phenomenon in which multiple and diverse phenotypic outcomes are influenced by a single gene (or single gene product.)Gene Expression Profiling: The determination of the pattern of genes expressed at the level of GENETIC TRANSCRIPTION, under specific circumstances or in a specific cell.Models, Psychological: Theoretical representations that simulate psychological processes and/or social processes. These include the use of mathematical equations, computers, and other electronic equipment.Prospective Studies: Observation of a population for a sufficient number of persons over a sufficient number of years to generate incidence or mortality rates subsequent to the selection of the study group.Pedigree: The record of descent or ancestry, particularly of a particular condition or trait, indicating individual family members, their relationships, and their status with respect to the trait or condition.Population Density: Number of individuals in a population relative to space.Litter Size: The number of offspring produced at one birth by a viviparous animal.Materials Testing: The testing of materials and devices, especially those used for PROSTHESES AND IMPLANTS; SUTURES; TISSUE ADHESIVES; etc., for hardness, strength, durability, safety, efficacy, and biocompatibility.Oligonucleotide Array Sequence Analysis: Hybridization of a nucleic acid sample to a very large set of OLIGONUCLEOTIDE PROBES, which have been attached individually in columns and rows to a solid support, to determine a BASE SEQUENCE, or to detect variations in a gene sequence, GENE EXPRESSION, or for GENE MAPPING.Quality of Life: A generic concept reflecting concern with the modification and enhancement of life attributes, e.g., physical, political, moral and social environment; the overall condition of a human life.Cluster Analysis: A set of statistical methods used to group variables or observations into strongly inter-related subgroups. In epidemiology, it may be used to analyze a closely grouped series of events or cases of disease or other health-related phenomenon with well-defined distribution patterns in relation to time or place or both.Body Mass Index: An indicator of body density as determined by the relationship of BODY WEIGHT to BODY HEIGHT. BMI=weight (kg)/height squared (m2). BMI correlates with body fat (ADIPOSE TISSUE). Their relationship varies with age and gender. For adults, BMI falls into these categories: below 18.5 (underweight); 18.5-24.9 (normal); 25.0-29.9 (overweight); 30.0 and above (obese). (National Center for Health Statistics, Centers for Disease Control and Prevention)Normal Distribution: Continuous frequency distribution of infinite range. Its properties are as follows: 1, continuous, symmetrical distribution with both tails extending to infinity; 2, arithmetic mean, mode, and median identical; and 3, shape completely determined by the mean and standard deviation.Binomial Distribution: The probability distribution associated with two mutually exclusive outcomes; used to model cumulative incidence rates and prevalence rates. The Bernoulli distribution is a special case of binomial distribution.Doppler Effect: Changes in the observed frequency of waves (as sound, light, or radio waves) due to the relative motion of source and observer. The effect was named for the 19th century Austrian physicist Johann Christian Doppler.Predictive Value of Tests: In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test.Polymorphism, Genetic: The regular and simultaneous occurrence in a single interbreeding population of two or more discontinuous genotypes. The concept includes differences in genotypes ranging in size from a single nucleotide site (POLYMORPHISM, SINGLE NUCLEOTIDE) to large nucleotide sequences visible at a chromosomal level.Dental Stress Analysis: The description and measurement of the various factors that produce physical stress upon dental restorations, prostheses, or appliances, materials associated with them, or the natural oral structures.Signal-To-Noise Ratio: The comparison of the quantity of meaningful data to the irrelevant or incorrect data.Social Environment: The aggregate of social and cultural institutions, forms, patterns, and processes that influence the life of an individual or community.Cognition: Intellectual or mental process whereby an organism obtains knowledge.Orthodontic Brackets: Small metal or ceramic attachments used to fasten an arch wire. These attachments are soldered or welded to an orthodontic band or cemented directly onto the teeth. Bowles brackets, edgewise brackets, multiphase brackets, ribbon arch brackets, twin-wire brackets, and universal brackets are all types of orthodontic brackets.Body Composition: The relative amounts of various components in the body, such as percentage of body fat.Psychomotor Performance: The coordination of a sensory or ideational (cognitive) process and a motor activity.Brain: The part of CENTRAL NERVOUS SYSTEM that is contained within the skull (CRANIUM). Arising from the NEURAL TUBE, the embryonic brain is comprised of three major parts including PROSENCEPHALON (the forebrain); MESENCEPHALON (the midbrain); and RHOMBENCEPHALON (the hindbrain). The developed brain consists of CEREBRUM; CEREBELLUM; and other structures in the BRAIN STEM.Heredity: The transmission of traits encoded in GENES from parent to offspring.Statistics, Nonparametric: A class of statistical methods applicable to a large set of probability distributions used to test for correlation, location, independence, etc. In most nonparametric statistical tests, the original scores or observations are replaced by another variable containing less information. An important class of nonparametric tests employs the ordinal properties of the data. Another class of tests uses information about whether an observation is above or below some fixed value such as the median, and a third class is based on the frequency of the occurrence of runs in the data. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 4th ed, p1284; Corsini, Concise Encyclopedia of Psychology, 1987, p764-5)Lod Score: The total relative probability, expressed on a logarithmic scale, that a linkage relationship exists among selected loci. Lod is an acronym for "logarithmic odds."Animal Husbandry: The science of breeding, feeding and care of domestic animals; includes housing and nutrition.Models, Neurological: Theoretical representations that simulate the behavior or activity of the neurological system, processes or phenomena; includes the use of mathematical equations, computers, and other electronic equipment.Adaptation, Psychological: A state of harmony between internal needs and external demands and the processes used in achieving this condition. (From APA Thesaurus of Psychological Index Terms, 8th ed)Movement: The act, process, or result of passing from one place or position to another. It differs from LOCOMOTION in that locomotion is restricted to the passing of the whole body from one place to another, while movement encompasses both locomotion but also a change of the position of the whole body or any of its parts. Movement may be used with reference to humans, vertebrate and invertebrate animals, and microorganisms. Differentiate also from MOTOR ACTIVITY, movement associated with behavior.Orthodontic Wires: Wires of various dimensions and grades made of stainless steel or precious metal. They are used in orthodontic treatment.Genetic Drift: The fluctuation of the ALLELE FREQUENCY from one generation to the next.Birth Weight: The mass or quantity of heaviness of an individual at BIRTH. It is expressed by units of pounds or kilograms.Research Design: A plan for collecting and utilizing data so that desired information can be obtained with sufficient precision or so that an hypothesis can be tested properly.Stress, Psychological: Stress wherein emotional factors predominate.Body Size: The physical measurements of a body.Haplotypes: The genetic constitution of individuals with respect to one member of a pair of allelic genes, or sets of genes that are closely linked and tend to be inherited together such as those of the MAJOR HISTOCOMPATIBILITY COMPLEX.Genetics, Behavioral: The experimental study of the relationship between the genotype of an organism and its behavior. The scope includes the effects of genes on simple sensory processes to complex organization of the nervous system.Case-Control Studies: Studies which start with the identification of persons with a disease of interest and a control (comparison, referent) group without the disease. The relationship of an attribute to the disease is examined by comparing diseased and non-diseased persons with regard to the frequency or levels of the attribute in each group.Posture: The position or attitude of the body.Population: The total number of individuals inhabiting a particular region or area.Software: Sequential operating programs and data which instruct the functioning of a digital computer.Depression: Depressive states usually of moderate intensity in contrast with major depression present in neurotic and psychotic disorders.Weight Gain: Increase in BODY WEIGHT over existing weight.Family: A social group consisting of parents or parent substitutes and children.Artifacts: Any visible result of a procedure which is caused by the procedure itself and not by the entity being analyzed. Common examples include histological structures introduced by tissue processing, radiographic images of structures that are not naturally present in living tissue, and products of chemical reactions that occur during analysis.United StatesPregnancy: The status during which female mammals carry their developing young (EMBRYOS or FETUSES) in utero before birth, beginning from FERTILIZATION to BIRTH.Individuality: Those psychological characteristics which differentiate individuals from one another.Seasons: Divisions of the year according to some regularly recurrent phenomena usually astronomical or climatic. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 6th ed)Treatment Outcome: Evaluation undertaken to assess the results or consequences of management and procedures used in combating disease in order to determine the efficacy, effectiveness, safety, and practicability of these interventions in individual cases or series.European Continental Ancestry Group: Individuals whose ancestral origins are in the continent of Europe.Anthropometry: The technique that deals with the measurement of the size, weight, and proportions of the human or other primate body.Self Efficacy: Cognitive mechanism based on expectations or beliefs about one's ability to perform actions necessary to produce a given effect. It is also a theoretical component of behavior change in various therapeutic treatments. (APA, Thesaurus of Psychological Index Terms, 1994)Fertility: The capacity to conceive or to induce conception. It may refer to either the male or female.Ulna: The inner and longer bone of the FOREARM.Poisson Distribution: A distribution function used to describe the occurrence of rare events or to describe the sampling distribution of isolated counts in a continuum of time or space.Task Performance and Analysis: The detailed examination of observable activity or behavior associated with the execution or completion of a required function or unit of work.Activities of Daily Living: The performance of the basic activities of self care, such as dressing, ambulation, or eating.Sampling Studies: Studies in which a number of subjects are selected from all subjects in a defined population. Conclusions based on sample results may be attributed only to the population sampled.Personality Inventory: Check list, usually to be filled out by a person about himself, consisting of many statements about personal characteristics which the subject checks.Geography: The science dealing with the earth and its life, especially the description of land, sea, and air and the distribution of plant and animal life, including humanity and human industries with reference to the mutual relations of these elements. (From Webster, 3d ed)Personality: Behavior-response patterns that characterize the individual.Body Constitution: The physical characteristics of the body, including the mode of performance of functions, the activity of metabolic processes, the manner and degree of reactions to stimuli, and power of resistance to the attack of pathogenic organisms.Disability Evaluation: Determination of the degree of a physical, mental, or emotional handicap. The diagnosis is applied to legal qualification for benefits and income under disability insurance and to eligibility for Social Security and workmen's compensation benefits.Reaction Time: The time from the onset of a stimulus until a response is observed.Siblings: Persons or animals having at least one parent in common. (American College Dictionary, 3d ed)Anxiety: Feeling or emotion of dread, apprehension, and impending disaster but not disabling as with ANXIETY DISORDERS.Markov Chains: A stochastic process such that the conditional probability distribution for a state at any future instant, given the present state, is unaffected by any additional knowledge of the past history of the system.Dental Alloys: A mixture of metallic elements or compounds with other metallic or metalloid elements in varying proportions for use in restorative or prosthetic dentistry.Self Concept: A person's view of himself.Demography: Statistical interpretation and description of a population with reference to distribution, composition, or structure.Health Status: The level of health of the individual, group, or population as subjectively assessed by the individual or by more objective measures.Swine: Any of various animals that constitute the family Suidae and comprise stout-bodied, short-legged omnivorous mammals with thick skin, usually covered with coarse bristles, a rather long mobile snout, and small tail. Included are the genera Babyrousa, Phacochoerus (wart hogs), and Sus, the latter containing the domestic pig (see SUS SCROFA).Statistical Distributions: The complete summaries of the frequencies of the values or categories of a measurement made on a group of items, a population, or other collection of data. The distribution tells either how many or what proportion of the group was found to have each value (or each range of values) out of all the possible values that the quantitative measure can have.Image Interpretation, Computer-Assisted: Methods developed to aid in the interpretation of ultrasound, radiographic images, etc., for diagnosis of disease.Heterozygote: An individual having different alleles at one or more loci regarding a specific character.Body Height: The distance from the sole to the crown of the head with body standing on a flat surface and fully extended.Psychiatric Status Rating Scales: Standardized procedures utilizing rating scales or interview schedules carried out by health personnel for evaluating the degree of mental illness.Cognition Disorders: Disturbances in mental processes related to learning, thinking, reasoning, and judgment.Muscle, Skeletal: A subtype of striated muscle, attached by TENDONS to the SKELETON. Skeletal muscles are innervated and their movement can be consciously controlled. They are also called voluntary muscles.Fingers: Four or five slender jointed digits in humans and primates, attached to each HAND.Species Specificity: The restriction of a characteristic behavior, anatomical structure or physical system, such as immune response; metabolic response, or gene or gene variant to the members of one species. It refers to that property which differentiates one species from another but it is also used for phylogenetic levels higher or lower than the species.Blood Pressure: PRESSURE of the BLOOD on the ARTERIES and other BLOOD VESSELS.Range of Motion, Articular: The distance and direction to which a bone joint can be extended. Range of motion is a function of the condition of the joints, muscles, and connective tissues involved. Joint flexibility can be improved through appropriate MUSCLE STRETCHING EXERCISES.Signal Processing, Computer-Assisted: Computer-assisted processing of electric, ultrasonic, or electronic signals to interpret function and activity.Random Allocation: A process involving chance used in therapeutic trials or other research endeavor for allocating experimental subjects, human or animal, between treatment and control groups, or among treatment groups. It may also apply to experiments on inanimate objects.Resin Cements: Dental cements composed either of polymethyl methacrylate or dimethacrylate, produced by mixing an acrylic monomer liquid with acrylic polymers and mineral fillers. The cement is insoluble in water and is thus resistant to fluids in the mouth, but is also irritating to the dental pulp. It is used chiefly as a luting agent for fabricated and temporary restorations. (Jablonski's Dictionary of Dentistry, 1992, p159)Pain Measurement: Scales, questionnaires, tests, and other methods used to assess pain severity and duration in patients or experimental animals to aid in diagnosis, therapy, and physiological studies.Genes, Dominant: Genes that influence the PHENOTYPE both in the homozygous and the heterozygous state.Follow-Up Studies: Studies in which individuals or populations are followed to assess the outcome of exposures, procedures, or effects of a characteristic, e.g., occurrence of disease.Motor Activity: The physical activity of a human or an animal as a behavioral phenomenon.Socioeconomic Factors: Social and economic factors that characterize the individual or group within the social structure.Obesity: A status with BODY WEIGHT that is grossly above the acceptable or desirable weight, usually due to accumulation of excess FATS in the body. The standards may vary with age, sex, genetic or cultural background. In the BODY MASS INDEX, a BMI greater than 30.0 kg/m2 is considered obese, and a BMI greater than 40.0 kg/m2 is considered morbidly obese (MORBID OBESITY).Hand Strength: Force exerted when gripping or grasping.Biological Markers: Measurable and quantifiable biological parameters (e.g., specific enzyme concentration, specific hormone concentration, specific gene phenotype distribution in a population, presence of biological substances) which serve as indices for health- and physiology-related assessments, such as disease risk, psychiatric disorders, environmental exposure and its effects, disease diagnosis, metabolic processes, substance abuse, pregnancy, cell line development, epidemiologic studies, etc.Exercise: Physical activity which is usually regular and done with the intention of improving or maintaining PHYSICAL FITNESS or HEALTH. Contrast with PHYSICAL EXERTION which is concerned largely with the physiologic and metabolic response to energy expenditure.Sexual Behavior, Animal: Sexual activities of animals.Intention: What a person has in mind to do or bring about.Biostatistics: The application of STATISTICS to biological systems and organisms involving the retrieval or collection, analysis, reduction, and interpretation of qualitative and quantitative data.Nuclear Family: A family composed of spouses and their children.Quality Control: A system for verifying and maintaining a desired level of quality in a product or process by careful planning, use of proper equipment, continued inspection, and corrective action as required. (Random House Unabridged Dictionary, 2d ed)Numerical Analysis, Computer-Assisted: Computer-assisted study of methods for obtaining useful quantitative solutions to problems that have been expressed mathematically.Genetic Association Studies: The analysis of a sequence such as a region of a chromosome, a haplotype, a gene, or an allele for its involvement in controlling the phenotype of a specific trait, metabolic pathway, or disease.Mothers: Female parents, human or animal.Orthodontic Appliance Design: The planning, calculation, and creation of an apparatus for the purpose of correcting the placement or straightening of teeth.Environmental Monitoring: The monitoring of the level of toxins, chemical pollutants, microbial contaminants, or other harmful substances in the environment (soil, air, and water), workplace, or in the bodies of people and animals present in that environment.Retrospective Studies: Studies used to test etiologic hypotheses in which inferences about an exposure to putative causal factors are derived from data relating to characteristics of persons under study or to events or experiences in their past. The essential feature is that some of the persons under study have the disease or outcome of interest and their characteristics are compared with those of unaffected persons.Fatigue: The state of weariness following a period of exertion, mental or physical, characterized by a decreased capacity for work and reduced efficiency to respond to stimuli.Weights and Measures: Measuring and weighing systems and processes.Ecosystem: A functional system which includes the organisms of a natural community together with their environment. (McGraw Hill Dictionary of Scientific and Technical Terms, 4th ed)Phylogeny: The relationships of groups of organisms as reflected by their genetic makeup.Population Dynamics: The pattern of any process, or the interrelationship of phenomena, which affects growth or change within a population.Calibration: Determination, by measurement or comparison with a standard, of the correct value of each scale reading on a meter or other measuring instrument; or determination of the settings of a control device that correspond to particular values of voltage, current, frequency or other output.Imaging, Three-Dimensional: The process of generating three-dimensional images by electronic, photographic, or other methods. For example, three-dimensional images can be generated by assembling multiple tomographic images with the aid of a computer, while photographic 3-D images (HOLOGRAPHY) can be made by exposing film to the interference pattern created when two laser light sources shine on an object.Psychological Tests: Standardized tests designed to measure abilities, as in intelligence, aptitude, and achievement tests, or to evaluate personality traits.Motor Skills: Performance of complex motor acts.Genome, Human: The complete genetic complement contained in the DNA of a set of CHROMOSOMES in a HUMAN. The length of the human genome is about 3 billion base pairs.

Comparative total mortality in 25 years in Italian and Greek middle aged rural men. (1/37255)

STUDY OBJECTIVE: Mortality over 25 years has been low in the Italian and very low in the Greek cohorts of the Seven Countries Study; factors responsible for this particularity were studied in detail. PARTICIPANTS AND SETTINGS: 1712 Italian and 1215 Greek men, aged 40-59 years, cohorts of the Seven Countries Study, representing over 95% of the populations in designated rural areas. DESIGN: Entry (1960-61) data included age, systolic blood pressure (SBP), smoking habits, total serum cholesterol, body mass index (BMI), arm circumference, vital capacity (VC), and forced expiratory volume in 3/4 seconds (FEV); the same data were obtained 10 years later. Multivariate Cox analysis was performed with all causes death in 25 years as end point. MAIN RESULTS: Italian men had higher entry levels of SBP, arm circumference, BMI, and VC; Greek men had higher cholesterol levels, smoking habits, and FEV. Mortality of Italian men was higher throughout; at 25 years cumulative mortality was 48.3% and 35.3% respectively. Coronary heart disease and stroke mortality increased fivefold in Italy and 10-fold in Greece between years 10 and 25. The only risk factor with a significantly higher contribution to mortality in Italian men was cholesterol. However, differences in entry SBP (higher in Italy) and FEV (higher in Greece) accounted for, according to the Lee method, 75% of the differential mortality between the two populations. At 10 years increases in SBP, cholesterol, BMI, and decreases in smoking habits, VC, FEV, and arm circumference had occurred (deltas). SBP increased more and FEV and VC decreased more in Italy than in Greece. Deltas, fed stepwise in the original model for the prediction of 10 to 25 years mortality, were significant for SBP, smoking, arm circumference, and VC in Greece, and for SBP and VC in Italy. CONCLUSION: Higher mortality in Italian men is related to stronger positive effects of entry SBP and weaker negative (protective) effects of FEV; in addition 10 year increases in SBP are higher and 10 year decreases in FEV are larger in Italy. Unaccounted factors, however, related to, for example, differences in the diet, may also have contributed to the differential mortality of these two Mediterranean populations.  (+info)

Activity-dependent metaplasticity of inhibitory and excitatory synaptic transmission in the lamprey spinal cord locomotor network. (2/37255)

Paired intracellular recordings have been used to examine the activity-dependent plasticity and neuromodulator-induced metaplasticity of synaptic inputs from identified inhibitory and excitatory interneurons in the lamprey spinal cord. Trains of spikes at 5-20 Hz were used to mimic the frequency of spiking that occurs in network interneurons during NMDA or brainstem-evoked locomotor activity. Inputs from inhibitory and excitatory interneurons exhibited similar activity-dependent changes, with synaptic depression developing during the spike train. The level of depression reached was greater with lower stimulation frequencies. Significant activity-dependent depression of inputs from excitatory interneurons and inhibitory crossed caudal interneurons, which are central elements in the patterning of network activity, usually developed between the fifth and tenth spikes in the train. Because these interneurons typically fire bursts of up to five spikes during locomotor activity, this activity-dependent plasticity will presumably not contribute to the patterning of network activity. However, in the presence of the neuromodulators substance P and 5-HT, significant activity-dependent metaplasticity of these inputs developed over the first five spikes in the train. Substance P induced significant activity-dependent depression of inhibitory but potentiation of excitatory interneuron inputs, whereas 5-HT induced significant activity-dependent potentiation of both inhibitory and excitatory interneuron inputs. Because these metaplastic effects are consistent with the substance P and 5-HT-induced modulation of the network output, activity-dependent metaplasticity could be a potential mechanism underlying the coordination and modulation of rhythmic network activity.  (+info)

The significance of non-significance. (3/37255)

We discuss the implications of empirical results that are statistically non-significant. Figures illustrate the interrelations among effect size, sample sizes and their dispersion, and the power of the experiment. All calculations (detailed in Appendix) are based on actual noncentral t-distributions, with no simplifying mathematical or statistical assumptions, and the contribution of each tail is determined separately. We emphasize the importance of reporting, wherever possible, the a priori power of a study so that the reader can see what the chances were of rejecting a null hypothesis that was false. As a practical alternative, we propose that non-significant inference be qualified by an estimate of the sample size that would be required in a subsequent experiment in order to attain an acceptable level of power under the assumption that the observed effect size in the sample is the same as the true effect size in the population; appropriate plots are provided for a power of 0.8. We also point out that successive outcomes of independent experiments each of which may not be statistically significant on its own, can be easily combined to give an overall p value that often turns out to be significant. And finally, in the event that the p value is high and the power sufficient, a non-significant result may stand and be published as such.  (+info)

Capture-recapture models including covariate effects. (4/37255)

Capture-recapture methods are used to estimate the incidence of a disease, using a multiple-source registry. Usually, log-linear methods are used to estimate population size, assuming that not all sources of notification are dependent. Where there are categorical covariates, a stratified analysis can be performed. The multinomial logit model has occasionally been used. In this paper, the authors compare log-linear and logit models with and without covariates, and use simulated data to compare estimates from different models. The crude estimate of population size is biased when the sources are not independent. Analyses adjusting for covariates produce less biased estimates. In the absence of covariates, or where all covariates are categorical, the log-linear model and the logit model are equivalent. The log-linear model cannot include continuous variables. To minimize potential bias in estimating incidence, covariates should be included in the design and analysis of multiple-source disease registries.  (+info)

Effect of coronary occlusion on left ventricular function with and without collateral supply during beating heart coronary artery surgery. (5/37255)

OBJECTIVE: To study the effects of coronary occlusion and collateral supply on left ventricular (LV) function during beating heart coronary artery surgery. DESIGN: Prospective intraoperative study, performed at baseline, during wall stabilisation, coronary artery occlusion, and 2 and 10 minutes after reperfusion. Transoesophageal M mode echocardiograms, simultaneous high fidelity LV pressure, and thermodilution cardiac output were measured. LV anterior wall thickening, thinning velocities, thickening fraction, regional work, and power production were derived. Asynchrony during the isovolumic periods was quantified as cycle efficiency. SETTING: Tertiary referral cardiac centre. PATIENTS: 14 patients with stable angina, mean (SD) age 62 (7) years, undergoing left anterior descending artery grafting using the "Octopus" device. RESULTS: Collaterals were absent in nine patients and present in five. Epicardial stabilisation did not affect LV function. Results are expressed as mean (SD). Coronary occlusion (15.6 (2) minutes) depressed anterior wall thickening (1.4 (0.6) v 2.6 (0.6) cm/s) and thinning velocities (1.4 (0.5) v 3.0 (0.6) cm/s), regional work (2.2 (0.8) v 4.6 (0.6) mJ/cm2), and power (21 (4) v 33 (5) mW/cm2) in patients without collaterals (p < 0.05 for all), but only wall thinning (3.5 (0.5) v 4.8 (0.5) cm/s, p < 0.05) in patients with collaterals. All returned to baseline within 10 minutes of reperfusion. Cycle efficiency and regional work were impaired at baseline and fell during occlusion, regardless of collaterals. Within 10 minutes of reperfusion both had increased above baseline. CONCLUSIONS: Coronary occlusion for up to 15 minutes during beating heart coronary artery surgery depressed standard measurements of systolic and diastolic anterior wall function in patients without collaterals, but only those of diastolic function in patients with collaterals. Regional synchrony decreased in both groups. All disturbances regressed within 10 minutes of reperfusion.  (+info)

Acquisition of nicotine discrimination and discriminative stimulus effects of nicotine in rats chronically exposed to caffeine. (6/37255)

Caffeine and nicotine are the main psychoactive ingredients of coffee and tobacco, with a high frequency of concurrent use in humans. This study examined the effects of chronic caffeine exposure on 1) rates of acquisition of a nicotine discrimination (0.1 or 0.4 mg/kg, s.c., training doses) and 2) the pharmacological characteristics of the established nicotine discrimination in male Sprague-Dawley rats. Once rats learned to lever-press reliably under a fixed ratio of 10 schedule for food pellets, they were randomly divided into two groups; 12 animals were maintained continuously on caffeine added to the drinking water (3 mg/ml) and another 12 control rats continued to drink tap water. In each group of water- and caffeine-drinking rats, there were six rats trained to discriminate 0.1 mg/kg of nicotine from saline and six rats trained to discriminate 0.4 mg/kg of nicotine from saline. Regardless of the training dose of nicotine, both water- and caffeine-drinking groups required a comparable number of training sessions to attain reliable stimulus control, although there was a trend for a slower acquisition in the caffeine-drinking group trained with 0.1 mg/kg of nicotine. Tests for generalization to different doses of nicotine revealed no significant differences in potency of nicotine between water- and caffeine-drinking groups. The nicotinic-receptor antagonist mecamylamine blocked the discriminative effects of 0.1 and 0.4 mg/kg nicotine with comparable potency and efficacy in water- and caffeine-drinking groups. There was a dose-related generalization to both the 0.1 and 0.4 mg/kg nicotine cue (maximum average of 51-83%) in water-drinking rats after i.p. treatment with d-amphetamine, cocaine, the selective dopamine uptake inhibitor GBR-12909, apomorphine, and the selective dopamine D1 receptor agonist SKF-82958, but not in caffeine-drinking rats (0-22%). There was no generalization to the nicotine cues after i.p. treatment with caffeine or the selective D2 (NPA) and D3 (PD 128,907) dopamine-receptor agonists in water- and caffeine-drinking rats. The dopamine-release inhibitor CGS 10746B reduced the discriminative effects of 0.4 mg/kg nicotine in water-drinking rats, but not in caffeine-drinking rats. There was no evidence of development of tolerance or sensitization to nicotine's effects throughout the study. In conclusion, chronic caffeine exposure (average, 135 mg/kg/day) did not affect the rate of acquisition of the nicotine discrimination, but it did reduce the dopaminergic component of the nicotine-discriminative cue. The reduction of the dopaminergic component of the nicotine cue was permanent, as this effect was still evident after the caffeine solution was replaced with water in caffeine-drinking rats. That nicotine could reliably serve as a discriminative stimulus in the absence of the dopaminergic component of its discriminative cue may differentiate nicotine from "classical dopaminergic" drugs of abuse such as cocaine and amphetamine.  (+info)

Hierarchical cluster analysis applied to workers' exposures in fiberglass insulation manufacturing. (7/37255)

The objectives of this study were to explore the application of cluster analysis to the characterization of multiple exposures in industrial hygiene practice and to compare exposure groupings based on the result from cluster analysis with that based on non-measurement-based approaches commonly used in epidemiology. Cluster analysis was performed for 37 workers simultaneously exposed to three agents (endotoxin, phenolic compounds and formaldehyde) in fiberglass insulation manufacturing. Different clustering algorithms, including complete-linkage (or farthest-neighbor), single-linkage (or nearest-neighbor), group-average and model-based clustering approaches, were used to construct the tree structures from which clusters can be formed. Differences were observed between the exposure clusters constructed by these different clustering algorithms. When contrasting the exposure classification based on tree structures with that based on non-measurement-based information, the results indicate that the exposure clusters identified from the tree structures had little in common with the classification results from either the traditional exposure zone or the work group classification approach. In terms of the defining homogeneous exposure groups or from the standpoint of health risk, some toxicological normalization in the components of the exposure vector appears to be required in order to form meaningful exposure groupings from cluster analysis. Finally, it remains important to see if the lack of correspondence between exposure groups based on epidemiological classification and measurement data is a peculiarity of the data or a more general problem in multivariate exposure analysis.  (+info)

Racial differences in the outcome of left ventricular dysfunction. (8/37255)

BACKGROUND: Population-based studies have found that black patients with congestive heart failure have a higher mortality rate than whites with the same condition. This finding has been attributed to differences in the severity, causes, and management of heart failure, the prevalence of coexisting conditions, and socioeconomic factors. Although these factors probably account for some of the higher mortality due to congestive heart failure among blacks, we hypothesized that racial differences in the natural history of left ventricular dysfunction might also have a role. METHODS: Using data from the Studies of Left Ventricular Dysfunction (SOLVD) prevention and treatment trials, in which all patients received standardized therapy and follow-up, we conducted a retrospective analysis of the outcomes of asymptomatic and symptomatic left ventricular systolic dysfunction among black and white participants. The mean (+/-SD) follow-up was 34.2+/-14.0 months in the prevention trial and 32.3+/-14.8 months in the treatment trial among the black and white participants. RESULTS: The overall mortality rates in the prevention trial were 8.1 per 100 person-years for blacks and 5.1 per 100 person years for whites. In the treatment trial, the rates were 16.7 per 100 person-years and 13.4 per 100 person-years, respectively. After adjustment for age, coexisting conditions, severity and causes of heart failure, and use of medications, blacks had a higher risk of death from all causes in both the SOLVD prevention trial (relative risk, 1.36; 95 percent confidence interval, 1.06 to 1.74; P=0.02) and the treatment trial (relative risk, 1.25; 95 percent confidence interval, 1.04 to 1.50; P=0.02). In both trials blacks were also at higher risk for death due to pump failure and for the combined end point of death from any cause or hospitalization for heart failure, our two predefined indicators of the progression of left ventricular systolic dysfunction. CONCLUSIONS: Blacks with mild-to-moderate left ventricular systolic dysfunction appear to be at higher risk for progression of heart failure and death from any cause than similarly treated whites. These results suggest that there may be racial differences in the outcome of asymptomatic and symptomatic left ventricular systolic dysfunction.  (+info)

*Analysis of variance

One-way analysis of variance Permutational analysis of variance Repeated measures ANOVA Two-way analysis of variance Variance ... analysis of molecular variance) Analysis of covariance (ANCOVA) ANORVA (analysis of rhythmic variance) ANOVA on ranks ANOVA- ... simultaneous component analysis Explained variation Mixed-design analysis of variance Multivariate analysis of variance (MANOVA ... His first application of the analysis of variance was published in 1921. Analysis of variance became widely known after being ...

*Permutational analysis of variance

Permutational multivariate analysis of variance (PERMANOVA), is a non-parametric multivariate statistical test. PERMANOVA is ... Anderson, Marti J. (2001). "A new method for non-parametric multivariate analysis of variance". Austral Ecology. 26 (1): 32-46 ... doi:10.1111/j.1442-9993.2001.01070.pp.x. Anderson, Marti J. (2005). "Permutational Analysis of Variance" (PDF). Alejandro ... measure the sum-of-squares within and between group and make use of F test to compare within-group to between-group variance. ...

*Multivariate analysis of variance

Where sums of squares appear in univariate analysis of variance, in multivariate analysis of variance certain positive-definite ... Multivariate Analysis of Variance (MANOVA) by Aaron French, Marcelo Macedo, John Poulsen, Tyler Waterson and Angela Yu, San ... In statistics, multivariate analysis of variance (MANOVA) is a procedure for comparing multivariate sample means. As a ... "Multivariate Analysis of Variance (MANOVA): I. Theory" (PDF). Retrieved 2011-03-22. Garson, G. David. "Multivariate GLM, MANOVA ...

*One-way analysis of variance

Analysis of variance F test (Includes a one-way ANOVA example) Mixed model Multivariate analysis of variance (MANOVA) Repeated ... a non-parametric alternative to this test should be used such as Kruskal-Wallis one-way analysis of variance. If the variances ... In statistics, one-way analysis of variance (abbreviated one-way ANOVA) is a technique that can be used to compare means of two ... An extension of one-way ANOVA is two-way analysis of variance that examines the influence of two different categorical ...

*Mixed-design analysis of variance

... variance due to being in different repeated measure conditions), SSerror (other variance), and SSBT*WT (variance of interaction ... When running an analysis of variance to analyse a data set, the data set should meet the following criteria: Normality: scores ... In statistics, a mixed-design analysis of variance model (also known as a split-plot ANOVA) is used to test for differences ... Homogeneity of variance: each population should have the same error variance. Sphericity of the covariance matrix: ensures the ...

*Two-way analysis of variance

Analysis of variance F test (Includes a one-way ANOVA example) Mixed model Multivariate analysis of variance (MANOVA) One-way ... In statistics, the two-way analysis of variance (ANOVA) is an extension of the one-way ANOVA that examines the influence of two ... Gelman, Andrew (February 2005). "Analysis of variance? why it is more important than ever". The Annals of Statistics. 33 (1): 1 ... Gelman, Andrew; Hill, Jennifer (18 December 2006). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge ...

*Kruskal-Wallis one-way analysis of variance

The parametric equivalent of the Kruskal-Wallis test is the one-way analysis of variance (ANOVA). A significant Kruskal-Wallis ... Daniel, Wayne W. (1990). "Kruskal-Wallis one-way analysis of variance by ranks". Applied Nonparametric Statistics (2nd ed.). ... unlike the analogous one-way analysis of variance. If the researcher can make the less stringent assumptions of an identically ... "Use of ranks in one-criterion variance analysis". Journal of the American Statistical Association. 47 (260): 583-621. doi: ...

*Analysis of molecular variance

... (AMOVA), is a statistical model for the molecular variation in a single species, typically ... Excoffier, L; Smouse, Pe; Quattro, Jm (Jun 1992). "Analysis of molecular variance inferred from metric distances among DNA ... This software allows for calculation of analyses such as AMOVA, as well as comparisons with other types of closely related ... Since developing AMOVA, Excoffier has written a program for running such analyses. This program, which runs on Windows is ...

*Analysis of rhythmic variance

... --ANORVA. A new simple method for detecting rhythms in biological time series. Analysis of ... In statistics, analysis of rhythmic variance (ANORVA) is a method for detecting rhythms in biological time series, published by ... ANORVA is based on the premise that the variance in groups of data from rhythmic variables is low when a time distance of one ...

*Variance-based sensitivity analysis

... of the output variance is caused by the variance in the first input, 20% by the variance in the second, and 10% due to ... Variance-based sensitivity analysis (often referred to as the Sobol method or Sobol indices, after Ilya M. Sobol) is a form of ... global sensitivity analysis. Working within a probabilistic framework, it decomposes the variance of the output of the model or ... Variance-based measures of sensitivity are attractive because they measure sensitivity across the whole input space (i.e. it is ...

*Two-moment decision model

Mean-variance analysis redirects here. For mean-variance portfolio theory, see Modern portfolio theory or Mutual fund ... these employ mean-variance analysis, and focus on the mean and variance of a portfolio's final value. Suppose that all relevant ... "A note on Feldstein's criticism of mean-variance analysis". Review of Economic Studies. 45 (1): 197-199. JSTOR 2297094. Sinn, H ... The two moments are almost always the mean-that is, the expected value, which is the first moment about zero-and the variance, ...

*Management by exception

Stimpson, P; Smith, A (2011). Budgetary control - variance analysis (Business and Management for the IB Diploma ed.). Cambridge ... Analysers consider two types of variances: adverse variance and favourable variance. Adverse variance "exists when the ... Anon (2011). "Management by Exception and Variance Analysis". Accounting explanation. Archived from the original on 2011. ... Rather than considering all variances, managers establish criteria to determine which variances are significant to focus on. ...

*Momentum accounting and triple-entry bookkeeping

Ijiri, Y. (1993), "Variance analysis and triple-entry bookkeeping." In: Yuji Ijiri (ed.), Creative and innovative approaches to ... 82-90 (in Dutch). Sousa Ferreira, A.C. de, M.O. Morais, M.C. Silva and R.R. do Santaos (2009), "Integrated analysis in three ... Melse, E. (2009-10-28), TEMA analysis of Lehman Brothers - Video in Dutch. Masterclass.. ...

*Location-scale family

Mayshar, J. (1978). "A Note on Feldstein's Criticism of Mean-Variance Analysis". Review of Economic Studies. 45 (1): 197-199. ... has zero mean and unit variance, then Y {\displaystyle Y} can be written as Y = d μ Y + σ Y X {\displaystyle Y{\stackrel {d ... and decision-making can be framed in terms of the means and the variances of the distributions. Often, location-scale families ...

*Yuji Ijiri

Ijiri, Y. (1993), "Variance analysis and triple-entry bookkeeping." In: Yuji Ijiri (ed.), Creative and innovative approaches to ...

*Scheffé's method

It is particularly useful in analysis of variance (a special case of regression analysis), and in constructing simultaneous ... Scheffé, H. (1999) [1959]. The Analysis of Variance. New York: Wiley. ISBN 0-471-34505-9. Scheffé's method This article ... Applied Regression Analysis (2nd ed.). John Wiley and Sons, Inc. p. 93. ISBN 9780471170822. Bohrer, Robert (1967). "On ... Draper and Smith, in their 'Applied Regression Analysis' (see references), indicate that 'r' should be in the equation in place ...

*Statistics education

Analysis of Variance (Anova); Statistical Process Control; Acceptance Sampling. The Centre for Innovation in Mathematics ... Such courses require a good course in real analysis, covering the proofs of the theory of calculus and topics like the uniform ... This involves thinking about the nature and quality of the data and, where the data came from, choosing appropriate analyses ... At the same time, statistics is concerned with evidence-based reasoning, particularly with the analysis of data. Therefore, ...

*Generalized randomized block design

"12 Multivariate analysis of variance". Multivariate analysis. Academic Press. ISBN 0-12-471250-9. Milliken, George A.; Johnson ... With replicates, interaction can be tested with the multivariate analysis of variance and coefficients in the linear model can ... Analysis of messy data. 2. New York: Van Nostrand Reinhold. Wilk, M. B. (June 1955). "The Randomization Analysis of a ... test for the block-treatment interaction in the analysis of variance (anova) of the RCBD. The distinction between RCBDs and ...

*Resampling (statistics)

The analysis of variance test". Biometrika. 29 (3-4): 322-335. doi:10.1093/biomet/29.3-4.322. Modern references: Collingridge, ... However, the bootstrap variance estimator is not as good as the jackknife or the balanced repeated replication (BRR) variance ... In the case of a unimodal variate the ratio of the jackknife variance to the sample variance tends to be distributed as one ... Instead of using the jackknife to estimate the variance, it may instead be applied to the log of the variance. This ...

*E. J. G. Pitman

The analysis of variance test. Biometrika 29, (1938), 322-335. The estimation of the location and scale parameters of a ...

*James H. Bray

1985). Multivariate Analysis of Variance. SAGE Publications. ISBN 9780803923102. "James H Bray, Ph.D". Baylor College of ...

*Direct material price variance

In variance analysis (accounting) direct material price variance is the difference between the standard cost and the actual ... Example and direct material usage variance#Example for computations of both components. Variance analysis (accounting). ... Direct material usage variance ,tx2=Direct material price variance ,tx3=Direct material total variance ,am1=720 ,am2=424 ,am3= ... It is one of the two components (the other is direct material usage variance) of direct material total variance. Let us assume ...

*Multivariate analysis of covariance

Multivariate analysis of variance (MANOVA). [3] Davis, K., 2003. Multiple analysis of variance (MANOVA) or multiple analysis of ... "Multivariate Analysis of Variance (MANOVA): I. Theory" (PDF). Retrieved 2011-03-22. Garson, G. David. "Multivariate GLM, MANOVA ... Multivariate analysis of covariance (MANCOVA) is an extension of analysis of covariance (ANCOVA) methods to cover cases where ... Homogeneity of variances: Each dependent variable must demonstrate similar levels of variance across each independent variable ...

*John Tukey

Fundamentals of exploratory analysis of variance. Wiley. ISBN 0-471-52735-1. OCLC 23180322. CS1 maint: Multiple names: authors ... He was awarded the IEEE Medal of Honor in 1982 "For his contributions to the spectral analysis of random processes and the fast ... Reviews of Graphical Analysis of Multiresponse Data: Talbot, M. (June 2000), Biometrics, 56 (2): 649-650, JSTOR 2677019 CS1 ... Though he believed in the utility of separating the two types of analysis, he pointed out that sometimes, especially in natural ...

*Mutual fund separation theorem

Under mean-variance analysis, it can be shown that every minimum-variance portfolio given a particular expected return (that is ... separation theorems can be obtained without the use of mean-variance analysis. For example, David Cass and Joseph Stiglitz ... This equation proves the two-fund separation theorem for mean-variance analysis. For a geometric interpretation, see the ... The portfolio return variance in the objective function can be written as σ 2 = X T V X , {\displaystyle \sigma ^{2}=X^{T}VX,} ...

*Margin of error

... is positive whenever a population is incompletely sampled and the outcome measure has positive variance (that ... 17-19 Sample Sizes, Margin of Error, Quantitative Analysis Archived 2012-01-21 at the Wayback Machine. Lohr, Sharon L. (1999). ... Sampling: Design and Analysis. Pacific Grove, California: Duxbury Press. p. 49. ISBN 0-534-35361-4. The margin of error of an ... The true standard error of the statistic is the square root of the true sampling variance of the statistic. These two may not ...
Variance analysis is the difference between standard cost and actual cost incurred during a given period. Variances analysis can be performed both at cost and revenues level. In other words, if a business owner wants to know what is his planned result and how it will look when comparing it with actual results so he can see the overall performance of the business.. For Example: ABC Company has its monthly sales short by $4000.00 as compared to the forecasted sales of $20,000. The percentage of change was 4000/20000 was 20%. This was due to the fact that business lost one big customer who used to buy the company products for $3,500.00 due to late deliveries of shipment to the customer. That resulted a miss in the forecast of sales.. This kind of variance analysis helps businesses to understand why there is was fluctuation in its business and what it can do make changes in order to prevent this in the future.. That was just one example of variance analysis that business can perform regularly, there ...
Running head: VARIANCE ANALYSIS Variance Analysis Amilca Simeon Grand Canyon University Variance Analysis This is a paper to explain the variance in the
As with any ANOVA, repeated measures ANOVA is used for comparing three or more means .However, repeated measures ANOVA is used when all subjects are measured under a number of different conditions. As the subject is exposed to each condition in turn , the measurement of the dependent variable is repeated .Using a standard ANOVA in this case result in inappropriate even incorrect conclusion ,because it fails to model the correlation between the repeated measures: the data violate the ANOVA assumption of independence. If any repeated factor is present, then repeated measures ANOVA should be used. In addition to determining that differences exist among the means, the repeated measurements ANOVA procedure provides multiple means comparisons that identify which particular means are different. Repeated measure ANOVA tools in Origin consider three possible designs: ...
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2. Repeated Measures ANOVA. Perform a repeated measures ANOVA using the High_School_Scores.sav data set. You will use Score_0 through Score_12 as your repeated measure (7 levels), and gender as a fixed factor. a. Is the.
View Notes - Managerial Accounting Homework Revew Chapter 11 Answer Key from BUSINESS ACG 2071 at Florida State College. Chapter 11 Standard Costs and Variance Analysis QUESTIONS E4. Material Price
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Several of Yaras purchase and sales contracts for commodities are, or have embedded terms and conditions which under IFRS are, accounted for as derivatives. The derivative elements of these contracts are presented under "Commodity-based derivatives gain/(loss)" in the condensed consolidated interim statement of income and are referenced in the variance analysis (see below) as "Special items.". "Other and eliminations" consists mainly of cross-segment eliminations, in addition to Yaras headquarter costs. Profits on sales from Upstream to Downstream and Industrial are not recognized in the Yara condensed consolidated interim statement of income before the products are sold to external customers. These internal profits are eliminated in the "Other and eliminations" segment.. Changes in "Other and eliminations" EBITDA therefore usually reflect changes in Upstream-sourced stock (volumes) held by Downstream and Industrial, but can also be affected by changes in Upstream margins on products sold to ...
Chapter 9 Loglinear Variance Models Model the Variance and the Mean of the Response About Loglinear Variance Models The Loglinear Variance personality of the Fit Model platform enables you to … - Selection from JMP 11 Fitting Linear Models [Book]
Any variances, positive or negative should trigger an investigation. A positive variance may not be beneficial to a firm. It may, for instance, result from a manager under-spending on training or marketing, which may have negative impacts on performance and profitability. An improvement in sales revenue may be the result of increased prices, which may make the business less attractive in the longer term.. ...
Video created by University of Illinois at Urbana-Champaign for the course Managerial Accounting: Tools for Facilitating and Guiding Business Decisions. After establishing goals, setting targets, and the budget, upper management uses variance ...
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Im having trouble figuring out the standard quantity and standard hours. Im not sure that the rest of my calculations are correct either. Then there are the actual variances themselves and while I have the formulas they dont.
In many cases this is complicated by the lack of advertised prices and small samples. In the end the result is likely to reveal that the area does not have substantial price variations so you need to repeat the process for the next area. The process may help us to find a suitable area for investment but what next? We need to know where all the available properties are located before we can make a decision about a potential investment.. It is boring and extremely time consuming and the results you get today will be out of date as the market changes. Mapping the location of the properties is not impossible but it is even more boring and time consuming without any real guarantee of success.. So the answer is simple, I have written a program to do it ALL! And this is what it does.. ...
Are you looking for easy accounting tutorial? Established since 2007, Accounting-Financial-Tax.com hosts more than 1300 articles (still growing), and has helped millions accounting student, teacher, junior accountants and small business owners, worldwide.. ...
Project Management Institute (PMI)® Professional Development Units (PDUs): This Webinar is eligible for 1.5 PMI® PDUs in the Technical category of the Talent Triangle. Event Description: In Microsoft Project, a baseline is like a "snapshot" of your project before you begin entering actual progress. In this MPUG webinar, you will learn the following: Best… ...
kirjanpito & Rahoitus Projects for $30 - $250. I have a confirmed budget with all line items, variables and fixed costs outlines for the year. What I need is a tool to report week how the actuals are performing against the budget target, where we ...
Contabilidade & Finanças Projects for $30 - $250. I have a confirmed budget with all line items, variables and fixed costs outlines for the year. What I need is a tool to report week how the actuals are performing against the budget target, where we ...
Companies prepare budgets so they can plan the evolution of their business. Budgeted costs allow them to set prices, project sales and estimate profits. For a wide variety of reasons, costs and revenues can come in higher or lower than calculated. Budget variance analysis addresses these differences and helps ...
Simsbury, CT (PRWEB) October 19, 2016 -- Veeder-Root, a leading provider of fueling equipment and services, announced today the rollout of a new
Theres often an important story hidden in the numbers that, if discovered at the right time, can tell a story that business managers want and need to see.
Exercise 18.3 (p. 513) has you consider an ANOVA model that does not assume that every group has the same underlying variance. But the model is applied to data that, it turns out, have fairly homogeneous variances, and therefore the basic conclusions do not change from the model with homogeneous variances assumed. The graph at right shows some data in which the assumption of homogeneous variances does matter. There are four groups with apparently quite different variances. For these data, Groups 2 and 3 have small variances, and therefore they might be credibly different if considered alone. But groups 1 and 4 have large variances, so if the model is forced to accommodate all four groups simultaneously with a single variance (i.e., a single precision parameter), then the estimated variances of Groups 2 and 3 will be too large. Consequently, the estimated means of Groups 2 and 3 will be uncertain because a wide range of candidate mean parameter values can accommodate the data when the variance ...
We have utilized the favorable signal-to-noise ratios provided by whole- cell recording, combined with variance analysis, to determine the pre- or postsynaptic actions of a variety of manipulations on unitary EPSPs evoked by low-intensity stimulation of afferents to CA1 pyramidal neurons in slices of hippocampus. Estimates of quantal content (mcv) were determined by calculating the ratio of the squared average unitary EPSP amplitude (determined from 150-275 responses) to the variance of these responses (M2/sigma 2), while quantal amplitudes (qcv) were estimated by calculating the ratio of the response variance to average EPSP size (sigma 2/M). Estimates of mcv were highly correlated with those determined using the method of failures (mf). With paired stimulation (50 msec interpulse interval) there was a significant facilitation of the second unitary EPSP, accompanied by an increase in mcv, but not qcv, suggesting that this facilitation was of presynaptic origin. Superfusion of hippocampal slices ...
Draft topic: subject to change Overview Where volume, price and exchange variance analysis is used in a different currency from the...
FOR MORE CLASSES VISIT \nwww.acc202mart.com\n\nACC 202 Week 1 Assignment Week One Exercises\nACC 202 Week 1 Assignment Week One Problems\nACC 202 Week 2 Assignment Article Summary\nACC 202 Week 2 Assignment Week Two Exercises\nACC 202 Week 2 Assignment Week Two Problems\nACC 202 Week 2 DQ 1 Certified Management\nACC 202 Week 3 Assignment Week Three Exercises\nACC 202 Week 3 Assignment Week Three Problems\nACC 202 Week 3 DQ 1 Budgeting\nACC 202 Week 4 Assignment Week Four Exercises\nACC 202 Week 4 Assignment Week Four Problems\nACC 202 Week 4 DQ 1 Variance Analysis\nACC 202 Week 5 Assignment Final Paper\nACC 202 Week 5 Assignment Week Five Exercises\nACC 202 Week 5 Assignment Week Five Problems\n Slideshow 7336235 by cmpunk6902
Downloadable! This paper discusses two optimal allocation problems. We consider different hypotheses of portfolio selection with stable distributed returns for each of them. In particular, we study the optimal allocation between a riskless return and risky stable distributed returns. Furthermore, we examine and compare the optimal allocation obtained with the Gaussian and the stable non-Gaussian distributional assumption for the risky return. KEY WORDS: optimal allocation, stochastic dominance, risk aversion, measure of risk, a stable distribution, domain of attraction, sub-Gaussian stable distributed, fund separation, normal distribution, mean variance analysis, safety-first analysis.
One of the hardest tasks in modern research is organizing large data sets from multiple sources, such as those generated from RNA-Seq, ChIP-Seq and variance analysis, in ways that facilitate discovery. We have developed a unique web application designed around community standards for storing and displaying different forms of NGS data, that contains a full suite of features for visualizing transcript expression, exploring the genomic context of transcripts, and linking these results to functional annotation. The software is a Ruby on Rails application freely available as open source. (Live Demo). ...
GENEWIZs full-service Sanger sequencing options include managing your project from primer design to variance analysis and report generation.
Ting in a significant main effect of training (p,0.05; Figure 1C). Maximal activity of bHAD tended to be higher post-training (p = 0.07) in both the LO
MANOVA (Multivariate Analysis of Variance) is used to model a combination of dependent variables. Use MANOVA in Excel with the XLSTAT software.
Two-way Analysis of Variance. Two-way ANOVA is a type of study design with one numerical outcome variable and two categorical explanatory variables. Slideshow 495973 by baba
Implemented are various tests for semi-parametric repeated measures and general MANOVA designs that do neither assume multivariate normality nor covariance homogeneity, i.e., the procedures are applicable for a wide range of general multivariate factorial designs.. ...
Joe Schmuller discusses an analytic technique for a design that extends matched samples called the Repeated Measures Analysis of Variance. Repeated measures is a research design in which each person in the study participates in every level of the independent variable. Joe breaksdown the variability we cant account for or what Statisticians refer as error.
... - Learn SAS in simple and easy steps. Overview, Environment, User Interface, Program Structure, Basic Syntax, Data Sets, Variables, Strings, Arrays, Numeric Functions, Operators, Loops, Decision Making, Functions, Input Methods, Macros, Dates and Times, SQL, Output Delivery System, Simulations, Histograms, Charts, Scatterplots, Boxplots, Arithmetic Mean, Standard Deviation, Frequency Distributions, Crosstabulations, T-tests, Variances, Linear Regression, Bland-Altman Analysis, Chi-Square, Fishers Exact Tests, One-Way Anova, Repeated Measure Analysis, Hypothesis Testing.
The Between-Groups Two-Way ANOVA enables you to assess the effects of two independent variables in just one study. In this design, each sample experiences a different combination of the levels of the independent variables. Joe shows you the concepts behind this technique and how to use Excels Tool Pak to analyze the data for two-variable studies.
Analysis of Variance Stata assignment help & homework + project assistance Analysis of Variance Assignment Help Introduction Analysis of variance (ANOVA) is an analysis tool utilized in stats that divides the aggregate irregularit
We explain Analysis of Variance/ANOVA with video tutorials and quizzes, using our Many Ways(TM) approach from multiple teachers.|p||span style=color: rgb(0, 0, 0); font-family: arial, sans, sans-serif; font-size: 13px; white-space: pre-wrap; |This lesson will introduce analysis of variance/ANOVA and test statistic F.|/span||/p|
This function calculates analysis of variance (ANOVA) for a two way randomized block experiment with repeated observations for each treatment/block cell. There are overall tests for differences between treatment means, between block means and block/treatment interaction. Multiple comparison methods are provided for pairs of treatment means.
Learning Objectives In this chapter you will learn how to analyze between more than two groups of subjects Analysis of variance (ANOVA) is a statistical test that is designed to examine means across more than two groups by comparing variances, based upon the variability in each sample and in the combined samples
Downloadable! The bounded character of time-use data poses a challenge to the analysis of variance based on classical linear models. This paper investigates a computationally simple variance decomposition technique suitable for these data. As a by-product of the analysis, a measure of fit for systems of time-demand equations that possesses several useful properties is proposed.
Definition of analysis of variances (ANOVA): General: Statistical technique for determining the degree of difference or similarity between two or more groups of data. It is based on the comparison of the average value of a common component.
Variance based main effect indices for each emulator.Main effect index of each emulator (rows) to each input (columns), describing the proportion of the output
An analysis of the variation between all of the variables used in an experiment. Analysis of variance is used in finance in several different ways, such as to forecasting the movements of security prices by first determining which factors influence stock fluctuations.
... (ANOVA) is a statistical method used to test differences between two or more means. It may seem odd that the technique is called Anal
Mean versus variance plot of power transformed data. Plot of the mean of the probe set signal intensities after applying the transformation by the associated v
How to compute sample variance (standard deviation) as samples arrive sequentially, avoiding numerical problems that could degrade accuracy.
The T-test is a statistical test that measures the significance of the difference between the means in two sets of data in relation to the variance of the...
Production Variance Analysis in SAP Controlling 2nd Edition, Buy Now in India Rs. 76, You SAVE 10%, Production Variance Analysis in SAP Controlling 2nd Edition, John Jordan Summary, Book Review Production Variance Analysis in SAP Controlling 2nd Edition, SAP Press, Hardback, 240, 9781592293810
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Radar charts are used for visual interpretation of data bearing multiple dimensions; data is compared by correlating and contrasting entities. The chart below is used for the variance analysis of products and services. Data plot colors are customized using cosmetic customization attributes.. ...
en] Analysis of the results of a data reconciliation program is made easier by extracting more information from the Jacobian matrix of the constraint equations. Standard deviation for all state variables (measured or not measured) is related to the standard deviation of measurements. Distinction between variables that are actually corrected by the validation process, and those that are merely derived from a single measurement is straightforward. Based on this information, decisions can be taken : deletion of unnecessary measurements, addition of new measurement points and their optimal selection, or identification of key measurements for which any enhancement of accuracy would result in significant improvement in the quality of the process validation ...
Posted By - Accenture Solutions Pvt Ltd. Keywords - Strategy consulting,Financial control,Senior Analyst,Balance Sheet analysis,Statutory reporting,Financial operations,professional services,Individual Contributor,Variance analysis,Operations. Job Description - |P| |B| Job Summary |/B| |/P| |P| You will be aligned with our Finance Operations vertical and help us in determining Financial outcome by collecting operational Data / Reports, whilst conducting Analysis and Reconciling transactions. |/P| |P| You will be working as a part of Finance Processes team which is responsible for procedures exercised by companies to imply Financial control by using measure like recording, verifying, reporting, etc. for transaction which affect Revenue, Expenditure, Assets and Liabilities. |/P| |P| You will be responsible for Reporting where in you will be accountable for profit & loss analysis, balance sheet analysis, variance analysis commentary, reconciliations, statutory reporting and consolidation of
This listed Engineering / Manufacturing Company seeks an Assistant Financial Manager to join their finance department. If you looking to gain listed company experience then apply today.. Qualifications: B.Com Honours - Non negotiable. Duties and Responsibilities:. Monthly financial and management reporting.. Manage the distribution financial reports.. Checking of all creditors and sundry reconciliation and payments.. Assisting with actual/plan variance analysis on a monthly basis.. Assisting in the preparation of annual financial statements.. Checking and authorisation of General Ledger and balance sheet reconciliations.. Fixed asset Capex applications, additions, disposal, depreciation etc.. Raising and authorising of all journals entries.. Result Variance analysis.. Maintain internal controls and compliance with company policies.. All adhoc work as and when requested.. Attending all communication sessions.. Interested candidates can forward their comprehensive written applications to the ...
Books Name: Probability and Statistics for Engineering and the Sciences Author: Jay L. devore Edition:9th ISBN-13: 978-1305251809 ISBN-10: 1305251806 What is the Specialty of this Book? There are several book on probability and statistics on… ...
Heritability is a measure of possible genetic advancement under selection. Estimation of variance components could imply partitioning of genetic variability over different sources of variation. This article describes statistical methods applied and some of the observations made on results of heritability and genetic variance analysis of rice yield and related traits of progenies derived from a cross between wild and cultivated rice. A completely random model was used to perform analysis of variances employing PROC GLM. Parent-offspring regression coefficient was calculated using PROC REG. The parent-offspring regression can be greatly influenced by environments resulting in higher or lower trait expression in the offspring relative to the parents. Hence the data was standardized using PROC STANDARD and regression coefficients were recalculated. Variance components for the statistical design were estimated using PROC MIXED. Phenotypic correlations were analyzed by applying PROC CORR. Normal ...
The resolution and variance properties of 2D models of electrical resistivity derived from magnetotelluric measurements are analysed with a truncated singular value decomposition (TSVD) scheme on a local subspace partly taking into account the non-linearity of the inverse problem.. The TSVD resolution and variance analysis is performed on a local subspace pertaining to one single cell of interest at a time. The trade-off between model variance and model resolution is used to determine a level of truncation by fixing a variance threshold.. Non-linear semi-axes describe the non-linear confidence surface in the directions of the model eigenvectors and replace the inverse singular values in the computation of model variances. The model variance of the cell considered is estimated from the sum of squares of the non-linear semi-axes up to the given variance threshold. This - in turn - gives the truncation level of the TSVD and the row of the model resolution matrix belonging to the considered cell can ...
Repeated measures ANOVA found no significant main effect of fat content and no interaction between fat content and diagnosis; however, a significant three-way interaction between fat content, diagnosis, and trial was observed. Post hoc analysis revealed a significant fat content by trial interaction within the AN group, suggesting a significant trial effect for the fat-free samples only with improving ability to detect fat-free samples over repeated trials. ...
Examines the concepts and practices of cost measurement: variable costing, cost-volume-profit analysis, setting goals and monitoring performance, standard costing, and variance analysis. Students learn how to work with multiple products; standard mix and mix variances; joint and by-product costing; measurement and control of overhead costs; and constructing operating, working capital, and capital budgets. Students study analysis in support of decisions, such as pricing, setting product line and customer profitability policy, sourcing of products and services, and matching costing systems to strategy. For MSA, GDPA, & MST Students this is the first managerial accounting course you will take. For MBA students, this potential elective course builds upon concepts learned in MBA 640 which is why it should be taken after completing or waiving MBA 640.. ...
This tutorial will show you how to use SPSS version 12.0 to perform a two factor, between- subjects analysis of variance and related post-hoc tests. This tutorial assumes that you have started SPSS (click on Start , All Programs , SPSS for Windows , SPSS 12.0 for Windows). The factorial analysis of variance (ANOVA) is an inferential statistical test that allows you to test if each of several independent variables have an effect on the dependent variable (called the main effects). It also allows you to determine if the main effects are independent of each other (i.e., it allows you to determine if two more independent variables interact with each other.) It assumes that the dependent variable has an interval or ratio scale, but it is often also used with ordinally scaled data. In this example, we will look at the results of an actual quasi-experiment. In the study, people were randomly assigned either to come to class all the time, or to never come to class and to get the lecture notes from the ...
Adams County is seeking a professional candidate to provide high level participation in the development process, presentation, and monitoring of the annual county budget, including complex analysis of historic and proposed expenditures and revenues, current year variance analysis, and projection of revenues and expenditures in future years. Budget duties are performed within the context of expert level development and implementation of budget policies through a wide variety of tools and relationships. REQUIREMENTS: • Experience: o Five (5) years of professional finance, budgeting, accounting or related experience. o Three (3) years public sector/local government experience is required. • Education and Training: Bachelors Degree from an accredited college or university with major course work in Accounting, Finance, Business Management, or a related field.. ...
Amenc, N. et Le Sourd V. (2002), Théorie du portefeuille et analyse de sa performance, Economica.. Broque, C.T. et van den Berg, A. (1992), Gestion de Portefeuille, Actions, obligations, options, de Boeck Université. Cobbaut, R. (1997), Théorie financière, Economica.. Knight, F.H. (1921), Risk, Uncertainty and Profit, Harper, New York.. Leibowitz, M. et Henriksson, R.D. (1989), "Portfolio Optimization with Shortfall Constraints: A Confidence-Limit Approach to Managing Downside Risk", Financial Analysts Journal, March-April, pp. 34-41.. Lintner, J. (1965), "The Valuation of Risky Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets", Review of Economics and Statistics, February, pp. 13-37.. Markowitz, H. M. (1959), Portfolio Selection: Efficient Diversification of Investment, John Wiley and Sons, reprinted 1991 by Basil Blackwell, Cambridge MA.. Markowitz, H. M. (1987), Mean Variance Analysis in Portfolio Choice and Capital Markets, Basil Blackwell, Cambridge ...
Apply to Account & Finance Professional Job in U & V Consulting Group. at Delhi. Find related Account & Finance Professional and Recruitment Services Industry Jobs in Delhi 2 to 7 Yrs experience with accounts, auditing, billing, finance, Asset Based Lending, Variance Analysis, Treasury Management,accountancy, rep, ting, Commercial Finance, Managerial Finance, Cash Flow, Funding, W, king Capital Management, Financial Structuring skills. #9999519
Basics of financial accounting. Preparation of balance sheet, income statement and flow of funds statement. Inventory valuation and depreciation methods. Basics of accounting. Definition of costs. Absorbtion cost techniques, with an emphasis on allocation of overhead in manufacturing organizations. Budgeting. Variance Analysis. Cost-Volume-Profit Analysis. Pricing decisions, special decisions based on incremental analysis ...
Prerequisites: ACC300, CIS116. This course will provide a study of advanced management accounting principles, various costing systems and approaches, decision-making tools and methodologies, and problem-solving projects/cases. Included is a review of variable costing and break-even analysis, standard costing and variance analysis, discounted cash flow (DCF) applications, ABC Costing, an activity-based approach to service department costing, further analysis of responsibility accounting and an introduction to target costing. One or more case studies or projects using Excel will be required.. ...
This book provides a protocol for conducting gauge repeatability and reproducibility (R&R) experiments. Such an experiment is required whenever a new test system is developed to monitor a manufacturing process. The protocol presented here is used to determine if the testing system is capable of monitoring the manufacturing process with the desired level of accuracy and precision. This protocol is not currently available in other books or technical reports. In addition to providing a protocol for testing a measurement system, the book presents an up-to-date summary of methods used to construct confidence intervals in normal-based random and mixed analysis of variance (ANOVA) models. Thus, this comprehensive book will be useful to scientists in all fields of application who wish to construct interval estimates for ANOVA model parameters. It includes approaches that can be applied to any ANOVA model ...
A base period is the initial period from which a variance analysis or trend line is calculated. The period selected to be the base period should have similar operational characteristics to the other periods included in the analysis, or else the comparison will have little relevance. The base period concept is also applied to the calculation of economic statistics, such as the consumer price index.. Related Courses. Cost Accounting Fundamentals ...
Anova for Unbalanced Data: An Overview. Shaw RG, Mitchell-Olds T. Ecology 74:6 (Sep., 1993); 1638-1645. [Abstract] [PDF]. Description: An analysis of variance model with multiple factors is very easy to analyze when the data is balanced, that is, when every combination of the factors has the same number of observations. If some combinations have more or fewer observations, you need to approach the ANOVA model very carefully. This article shows some of the issues you need to be aware of with unbalanced data.. Steve Miller. Biostatistics, Open Source and BI � an Interview with Frank Harrell. Description: This article, published in Information Management Online, February 25, 2009, offers a nice interview with Frank Harrell, a leading proponent of modern statistical methods. Excerpt: My correspondence with Frank provided the opportunity to ask him to do an interview for the OpenBI Forum. He graciously accepted, turning around deft responses to my sometimes ponderous questions in very short order. ...
Logistic regression on survrate data set with missing data. library(norm) # Make appropriate changes in file and variable names. #setwd ("G:\\Missing_Data") #Adjust this as needed x <- read.table("https://www.uvm.edu/~dhowell/StatPages/Missing_Data/Missing-Logistic/Missing-Logistic/survrateMissingNA.dat", header = TRUE) y <- as.matrix(x) #convert table to matrix cat("Logistic regression using 132 cases and missing data \n\n") z <-(summary(glm(formula = outcome01~survrate + gsi + avoid + intrus, binomial, data = x))) #Use original data with missing values attach(x) ## Important The following code will run m = 5 times. The data will be concatenated into ComFile and then analyzed. # Data Augmentation using norm.R m <- 5 #Number of imputations k <- 9 #Number of variables in raw data file l <- 5 #Number of variables actually used in regression CombFile <- matrix(nrow = 0, ncol = k) for (i in 1:m) { s <- prelim.norm(y) #get preliminary statistics for the analysis thetahat <-em.norm(s) #Get MLE for ...
Background: The post arrest syndrome is characterized, in part, by a systemic inflammatory state whose molecular mechanisms and association with survival remain poorly understood. A deeper understanding of cytokine activity post arrest may identify an early biomarker for outcomes as well as a potential therapeutic target.. Hypothesis: Cytokine elevation is associated with survival after cardiac arrest (CA) and ROSC.. Methods: One hundred eleven consecutive patients (pts) enrolled in the multicenter Characterization of Mitochondrial Injury after Cardiac Arrest (COMICA) study underwent serial serum measurements for IL-6, IL-8, IL-10, and TNFα via a Millipore Multiplex Human Cytokine Panel at Time 0 (T0) defined as upon arrival to the hospital, and 12, 24, 36, and 48 hours post ROSC. We assessed the ability (sensitivity, specificity, and area under the receiver operating curve (ROC)) of these cytokines drawn at T0 to predict survival to hospital discharge. A repeated measures ANOVA was fit with a ...
Materials and Methods: The roots of 72 human premolars were endodontically prepared and divided into 6 groups according to the combination of the main factors: adhesive (Ambar and Adper Single Bond 2) and moisture (dry, wet, and overwet). The posts were cemented and after 1 week, the roots were cross sectioned into 6 disks. Two disks each were obtained from the cervical, middle, and apical thirds, and the PBS test was carried out (0.5 mm/min; n = 8). The NL was evaluated by scanning electron microscopy after the immersion of specimens in 50% silver nitrate (n = 4). The failure pattern was examined on all debonded specimens. Data were analyzed by three-way repeated measures ANOVA and Tukeys test (5 ...
From Venables and Ripley (2002) p.165. N ,- c(0,1,0,1,1,1,0,0,0,1,1,0,1,1,0,0,1,0,1,0,1,1,0,0) P ,- c(1,1,0,0,0,1,0,1,1,1,0,0,0,1,0,1,1,0,0,1,0,1,1,0) K ,- c(1,0,0,1,0,1,1,0,0,1,0,1,0,1,1,0,0,0,1,1,1,0,1,0) yield ,- c(49.5,62.8,46.8,57.0,59.8,58.5,55.5,56.0,62.8,55.8,69.5,55.0, 62.0,48.8,45.5,44.2,52.0,51.5,49.8,48.8,57.2,59.0,53.2,56.0) npk ,- data.frame(block=gl(6,4), N=factor(N), P=factor(P), K=factor(K), yield=yield) ( npk.aov ,- aov(yield ~ block + N*P*K, npk) ) summary(npk.aov) coefficients(npk.aov) # Cochran and Cox (1957, p.164) # 3x3 factorial with ordered factors, each is average of 12. CC ,- data.frame( y = c(449, 413, 326, 409, 358, 291, 341, 278, 312)/12, P = ordered(gl(3, 3)), N = ordered(gl(3, 1, 9)) ) CC.aov ,- aov(y ~ N * P, data = CC , weights = rep(12, 9)) summary(CC.aov) # Split both main effects into linear and quadratic parts. summary(CC.aov, split = list(N = list(L = 1, Q = 2), P = list(L = 1, Q = 2))) # Split only the interaction summary(CC.aov, split = list("N:P" = ...
Focusing on the time-dependent variability, we performed a repeated-measures ANOVA where the slope was used as dependent variable and the sensorimotor context [S (perception vs. production)], the modality [M (auditory vs. visual)], and the number of intervals [N (one or four)] as within-subject factors. The results showed significant main effects for S [F(1,12) = 22.9, P , 0.0001], N [F(1,12) = 14.3, P = 0.003], and M [F(1,12) = 10.1, P = 0.008]. In addition, the S × M [F(1,12) = 7.1, P = 0.021] and the S × N interactions [F(1,12) = 5.9, P = 0.031] also showed significant effects. However, the M × N interaction [F(1,12) = 1.7, P = 0.215] was not significant. Thus the slope was larger for perceptual than for production tasks [t-test, t(51) = 4.83, P , 0.0001] and larger for the visual than for the auditory modality [t-test, t(51) = −3.18, P = 0.003]. Furthermore, a t-test between the tasks with single (CAT-STT) versus multiple (DIS-MTT) intervals, showed a significantly larger slope in the ...
Analysis of covariance (ANCOVA) combines the techniques of analysis of variance (ANOVA) with regression methods. This approach is applicable where the dependent variable or response variable is continuous and the factors are a mixture of continuous and categorical variables. The continuous variables are known as covariates, hence the term, analysis of covariance. In experimental design problems, such variables may be observable, but difficult or impossible to include in the design explicitly (not controllable) or they may be controllable and included in the (iterative) design process. For example in some experiments temperature might be included as a continuous variable (predictor) whereas in others (e.g. measuring the speed of light) the ambient temperature might be recorded at the start of each run and used to reduce the error variance in the resulting analysis, i.e. it is explanatory but not controlled. By reducing the error variance using the correlation that may exist between the covariate ...
In t-test, the difference between 2 sample means are tested for Significance. In ANOVA the differences between means of more than 2 samples are tested for significance. This is done by examining the variation within the whole groups of sample means. It consists of a comparison between 2 estimates of the overall variation (of the complete set of measurements included in the analyses), one estimate being based on the variance of sample means about the grand mean. The other based on the variance of the individual measurements about their treatment means. The first estimate is called treatment variance. The second estimate is called error variance. If the null hypothesis is true, the ratio of these estimates would approximate 1. If, on the other hand, the sample means estimates differ from the population or group means then the ratio would exceed 1, In practice, this ratio is calculated as F and the level of probability of obtaining such a ratio is determined if the null hypothesis were to be ...
Values are means ± SE. Cholinergic responses evoked by bath application of carbachol (10 μM for 5 min) in CA3 pyramidal neurons. Boldface numbers indicate P , 0.05 for carbachol-induced effects within individual cell types (repeated-measures ANOVA with post-tests: baseline, carbachol, and wash). Asterisks indicate P , 0.01 when compared with values in wild-type neurons (one-way ANOVA with post-tests). ...
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Proteomics Mass spectrometry, repeated measure analysis, clinical trial design, survival analysis, receptor binding models.. ...
Suppose S is a set of numbers whose mean value is X, and suppose x is an element of S. We wish to define the variance of x with respect to S as a measure of the degree to which x differs from the mean X. It turns out to be most useful to define the variance as the square of the difference between x and X. Well denote this by V(x,S) = (x-X)2. Furthermore, we define the variance of any subset s1 of S as the average of the variances of the elements of s1. Thus, given a set s of n numbers x1, x2, ..., xn, from a set S whose mean is X, the variance of s with respect to S is given by. ...
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I got a long scalp on ER2 near the moring lows and shorted YM near the top around 7:30am. ER2 was the better short today compared to YM which has a more bullish tone compared to the other indices today. XLE and Crude Oil are selling off as I type right now, but volume may be letting up for some consolidation or a bounce pretty soon. Could only trade the first 2 hours, gotta go to work. Im not sure what is going on with bonds in relation to trading correlations with the stock indices ...
Due to limited precision, accuracy, and variability in ordinal outcomes, it behooves researchers to use either 5-point, 7-point, or higher level Likert scales. With more options, more unique variance can be accounted for the in the analysis and statistical power is increased. One-sampled tests possess more statistical power than other between-subjects statistics because there is only one group being analyzed, no other independent groups are included ...
In the present study, a significant main effect of scalp location was found for P3 in all subjects. The finding that P3 was maximal at centroparietal and parietal sites is consistent with previous reports (4, 15, 32, 34). Late-latency RREP components (e.g., P3), also known as endogenous components, are associated with cognitive processing of the sensory information and are highly sensitive to cognitive factors (9, 15, 31, 34). Increased amplitude and decreased latency of P3 in the attend compared with the ignore condition has been observed in response to other sensory stimuli (3, 17, 25,27). Recently, similar effects of attention on the RREP P3 have been reported (15, 34). Consistent with previous studies, we found that P3 was identified in all subjects during the attend trial. However, during the ignore trial, three DLT patients and one Nor subject did not have an identifiable P3. P3 latency was significantly shorter during the attend trial compared with the ignore trial. The main effect of ...
The last 3 days in a row there have been good 3pm EST reversals on ES and the other indices. This trade works good on YM. Look for indications in the tick and volume around 2:54-3:07pm EST ...
Calculates the regression model analysis of the variance (ANOVA) values. Syntax SLR_ANOVA(X, Y, Intercept, Return_type) X is the...
Financial Definition of Portfolio variance and related terms: Weighted sum of the covariance and variances of the assets in a portfolio. . .
It is frequently necessary to test if k samples have equal variances. Equal variances across samples is called homogeneity of variances. Some statistical tests, for example the analysis of variance, assume that variances are equal across groups or samples. ...
Clarifying the Concepts 11-1. What is an ANOVA?Answer: An ANOVA is a hypothesis test with at least one nominal independent variable (with at leas...
Analysis of variance (ANOVA) for the assessment of the product, group and period effects, and 90% con fi dence intervals for the ratio of Cmax,
Yes I finished my course. It was a summer course and I made an A. I would like to thank you very much again for always going above and beyond to make sure I understood the question and answer. I would have not made an A if it wasnt for this website and your constant help. Thank you so much and for even wanting a follow up. It shows what kind of person/ tutor you really are ...
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Mixing as an operation in granular material technology During mixing of granular materials using different methods, due to the specific physical properties the components are located in certain places in mixed bed. The purpose of mixing is to conduct the systems different in densities and dimensions to the dynamic stable state, however, it is important that distances between mixed parts of the same components must be equal. A chess board pattern can be an example of the surface distribution of two-component granular system mixed ideally. Unfortunately, segregation a phenomenon that is counterbalancing the homogeneity causes that the achievement of such a mixing state, especially in non-homogenous conditions of materials is impossible [1, 3, 19, 27, 29, 30, 37]. In the mixing of granular materials that are widely used in the agricultural and food industry, a process of the mixed components allocation in the whole volume of bed is one of the most important issues [13, 20, 21, 22, 23, 24, 25]. Due ...
Intermediate. Dr. Matthew Hill, CMA, CTP, FP&A, Director, Arkansas State University Center for Treasury and Financial Analytics. Session Description. This is the second of two sessions on key cost accounting topics. Specific topics covered in this session include a review of:. ...
http://www.assignmentcloud.com/acc-310/acc-310-week-5-dq-2-fundamentals-of-variance-analysisComplete Exercise 16-28 and 16-32. Remember to complete all parts of the problems and report the results of your analysis. Do not forget to show the necessary steps and explain how your attained that outcome. Respond to at least two of your classmates postings.For more classes ...
Complete Exercise 16-28 and 16-32. Remember to complete all parts of the problems and report the results of your analysis. Do not forget to show the necessary steps and explain how your attained that outcome. Respond to at least two of your classmates postings ...
Results from the heterogeneous display condition confirmed response differences between sequentially and simultaneously presented stimuli suggesting the existence of suppressive interactions among nearby stimuli in extrastriate cortex, but the critical question in our study was whether homogeneous displays produced similar suppressive interactions. We submitted the mean signal changes for each subject to a repeated measures ANOVA on presentation condition (sequential vs. simultaneous) and display type condition (homogeneous vs. heterogeneous). This analysis revealed a significant main effect of presentation condition for all areas except area V1; V2: F(1, 6) = 7.48, p , .05; VP: F(1, 4) = 33.80, p , .01; V4: F(1, 6) = 11.84, p , .05 ( Figures 2 and 3A). However, importantly, there was a significant interaction of the presentation condition and display type condition in area V4, F(1, 6) = 7.57, p , .05, such that the response differences between sequential and simultaneous presentation conditions ...
Some basic results in probability and statistics. basic regression analysis. Linear regression with one independent variable. Inferences in regression analysis. Aptness of model and remedial measures. Topics in regression analysis - I. General regression and correlation analysis. Matrix appreach to simple regression analysis. Multiple regression. Polymonial regression. Indicator variables. Topics in regression analysis - II. Search for best set of independent variables. Normal correlation models. Basic analysis of variance. Single - factor analysis of variance. Analysis of factor effects. Implementation of ANOVA model. Topics in analysis of variance - I. Multifactor analysis of variance. Two factor analysis of variance. Analysis of two - factor studies. To pics in analysis of variance - II. Multifactor studies. Experimental designs. Completely randomized designs. Analysis of covariance for completely randomized designs. Randomized block designs. Latin square designs.
One of the key roles of costing systems is to support the evaluation of performance and facilitate appropriate resource allocations. Through participation in a comparative cost study, management at Springfield Hospital, known for its heavy focus on operational excellence, become aware of opportunities for further improvement. Analysis of the differences in costs, uses, and allocations of resources will inform management in the decision and implementation of strategic plans. This case stimulates reflections on the importance of costing systems, in particular Time-Driven Activity Based Costing, and variance analysis as decision support mechanisms ...
With so many challenges, budgeting and forecasting is often a frustrating and painful experience for many finance professionals, who have to also endure added pressure to improve costs, resources and performance through accuracy, efficient and better controls. It doesnt have to be this way.. Spreadsheets are often the go to tool with around 90% of businesses using excel. However, there are sophisticated tools and software that can help to make the budgeting and forecasting process much more efficient. Yes they do exist!. What are the challenges?. Challenge 1: Delivering Top Down Budget and Forecast targets from the detailed bottom-up budget process will often create target shortfalls which often get filled by high level budget adjustments which are generallly not owned by the budget holders. Challenge 2: Many Budget and Forecast processes do not incorporate customer and/or product level detail due to the complexity and volume of data which then makes sales and gross margin variance analysis ...
We present a novel generalized model for the analysis of noise with a known spectral density. This model is particularly appropriate for the analysis of noise with a 1/fα distribution. The noise model reveals that, for α , 1, 1/fα noise significantly impacts the signal-to-noise ratio (SNR) for integration times that near a characteristic time, beyond which the SNR will no longer significantly improve with increasing integration time. We experimentally verify our theoretical findings with a set of experiments employing a quadrature homodyne optical coherence tomography (OCT) system and find good agreement. The characteristic integration time is measured to be approximately 2 ms for our system. Additionally, we find that the 1/f noise characteristics, including the exponent, α, as well as the characteristic integration time, are system and photodetector dependent.. ©2007 Optical Society of America. Full Article , PDF Article ...
Discriminant function analysis is a statistical analysis to predict a categorical dependent variable (called a grouping variable) by one or more continuous or binary independent variables (called predictor variables). The original dichotomous discriminant analysis was developed by Sir Ronald Fisher in 1936. It is different from an ANOVA or MANOVA, which is used to predict one (ANOVA) or multiple (MANOVA) continuous dependent variables by one or more independent categorical variables. Discriminant function analysis is useful in determining whether a set of variables is effective in predicting category membership. Discriminant analysis is used when groups are known a priori (unlike in cluster analysis). Each case must have a score on one or more quantitative predictor measures, and a score on a group measure. In simple terms, discriminant function analysis is classification - the act of distributing things into groups, classes or categories of the same type. Moreover, it is a useful follow-up ...
BACKGROUND We performed a multicenter controlled trial to assess the knowledge and attitude (KA) about cardiopulmonary resuscitation (CPR) among secondary school children in a district in Malaysia. METHODS This was a prospective intervention study. The primary endpoint of the study was to determine the level of KA about resuscitation after CPR training. The six schools and classes from selected schools were chosen by randomization among the form three and four classes using sealed envelopes. A fully validated questionnaire consisting of three sections (sociodemographic, knowledge and attitude) was given to the pupils before and 2 weeks after the intervention. The intervention group was given a lecture, video show, pamphlet and 1-h practical session on CPR training. The control group received a placebo in order to overcome the learning effect. The maximum scores for the knowledge and attitude sections were 72 and 28, respectively. Repeated measures ANOVA analysis was used for specific objectives ...
Thomas Eric Duncan (May 2, 1969 - October 8, 2014) was a Liberian who became the first Ebola patient diagnosed in the United States on September 30, 2014. Duncan, who had been visiting family in Dallas, was treated at Texas Health Presbyterian Hospital Dallas. By October 4, Duncans condition had deteriorated from "serious but stable" to "critical". On October 8, Duncan died of Ebola. Two health care workers became infected with Ebola virus, 26-year-old nurse Nina Pham and 29-year-old nurse Amber Vinson, both of whom had taken care of him at Texas Health Presbyterian Hospital (THPH). Both have been cured. The family eventually threatened to sue the hospital based on the claim that Duncan had not received proper and timely care. The family was thus able to receive compensation from THPH. On November 10, 2014, Duncans family reached a "resolution" with THPH that included the hospital covering the expenses related to Duncans intensive and onerous treatment, as well as an undisclosed amount cash ...
The quality of the consumed drinking water may affect oral health. For example, the presence of iron in drinking water can cause aesthetic problems related to changes in dental enamel color. This study assessed the prevalence of extrinsic enamel color changes and their relationship with the quality of the water in the town of Caapiranga/AM-Brazil. Three hundred and forty six residents of the urban area were examined, and they also answered a questionnaire on eating habits and self-perceived oral health. As the initial results indicated an insufficient number of observations for the application of variance analysis (one-way ANOVA), the Student t test was chosen to compare levels of iron content in the water coming from two sources. The change in tooth color had a prevalence of 5.78% (20 people). The majority of the population (n = 261, 75.43%) consumed well water. Those who presented extrinsic stains were uncomfortable with the appearance of their teeth (15.09%). We conclude that while there is excess of
Objective The current research aimed to investigate the effectiveness of Sternbergs successful intelligence program upon working memory and executive functions of sharp-witted primary school students. The statistical population of the current research consisted of all sharp-witted male students of the city of Isfahan in the academic year of 2015-2016.Method For this purpose, totally 30 sharp-witted male students were selected through multi- stage cluster random sampling method and were randomly assigned to two experimental and control groups (15 students in the experimental group and another 15 students in the control group). The Sternbergs successful intelligence program was administered on the experimental group. The tools used for this research included software to measure working memory and questionnaire (inventory) on rating executive functions of the primary school students. To analyze the research data, multivariate covariance analysis (MANCOVA) was employed.Results Findings revealed that
TY - JOUR. T1 - Phosphodiesterase 2 and 5 inhibition attenuates the object memory deficit induced by acute tryptophan depletion. AU - van Donkelaar, E.L.. AU - Rutten, K.. AU - Blokland, A.. AU - Akkerman, S.. AU - Steinbusch, H.P.. AU - Prickaerts, J.H.H.J.. PY - 2008/1/1. Y1 - 2008/1/1. N2 - The underlying mechanism of short-term memory improvement after inhibition of specific phosphodiesterases (PDEs) is still poorly understood. The present study aimed to reveal the ability of PDE5 and PDE2 inhibitors, that increase cyclic guanosine morrophosphate (cGMP) and both cyclic adenosine monophosphate (cAMP) and cGMP, respectively, to reverse an object recognition deficit induced by acute tryptophan depletion. Acute tryptophan depletion is a pharmacological challenge tool to lower central serotonin (5-hydroxytryptamine; 5-HT) levels by depleting the availability of its dietary precursor tryptophan. Short-term object memory was tested in male Wistar rats by exposing them to the object recognition ...

VARIANCE ANALYSIS DEFINITIONVARIANCE ANALYSIS DEFINITION

VARIANCE ANALYSIS is the analysis of performance by means of variances. Used to promote management action at the earliest ... Variance analysis is the process of examining in detail each variance between actual and budgeted/expected/standard costs to ...
more infohttps://www.ventureline.com/accounting-glossary/V/variance-analysis-definition/

Variance Analysis in These Slow-Growth TimesVariance Analysis in These Slow-Growth Times

Financial Planning & Analysis. May 22, 2015 How to View Variance Analysis in These Slow-Growth Times. Counterintuitively, ... In this video he returns to the topic of variance analysis, explaining the fine points of different types of variances - in ... and in Conine-authored pieces on variance analysis, whether to cut volume or price, shareholder return, and, most recently, ...
more infohttps://www.cfo.com/financial-planning-analysis/2015/05/view-variance-analysis-slow-growth-times/

Problems in Variance Analysis -
	               		Exercise
                        - Harvard Business SchoolProblems in Variance Analysis - Exercise - Harvard Business School

"Problems in Variance Analysis." Harvard Business School Exercise 196-120, February 1996. ...
more infohttps://www.hbs.edu/faculty/Pages/item.aspx?num=4986

Analysis of variance - WikipediaAnalysis of variance - Wikipedia

His first application of the analysis of variance was published in 1921.[10] Analysis of variance became widely known after ... Textbook analysis using a normal distribution[edit]. The analysis of variance can be presented in terms of a linear model, ... variance within treatments. {\displaystyle F={\frac {\text{variance between treatments}}{\text{variance within treatments}}}}. ... Associated analysis[edit]. Some analysis is required in support of the design of the experiment while other analysis is ...
more infohttps://en.wikipedia.org/wiki/Analysis_of_variance

Variance Analysis - Lido CompanyVariance Analysis - Lido Company

... you need to compute these variances based on the 400 units which were. ... brainmass.com/statistics/analysis-of-variance/variance-analysis-lido-company-333459 Attachments. *E2 Acct.doc ... Variance Analysis - Lido Company. Add. Remove. This content was COPIED from BrainMass.com - View the original, and get the ... From the foregoing information, compute the following variances. Show whether the variance is favorable (F) or unfavorable (U): ...
more infohttps://brainmass.com/statistics/analysis-of-variance/variance-analysis-lido-company-333459

Analysis of variance - WikipediaAnalysis of variance - Wikipedia

His first application of the analysis of variance was published in 1921.[10] Analysis of variance became widely known after ... Textbook analysis using a normal distribution[edit]. The analysis of variance can be presented in terms of a linear model, ... variance within treatments. {\displaystyle F={\frac {\text{variance between treatments}}{\text{variance within treatments}}}}. ... Associated analysis[edit]. Some analysis is required in support of the design of the experiment while other analysis is ...
more infohttps://en.wikipedia.org/wiki/ANOVA

Variance Analysis Capabilities | TrintechVariance Analysis Capabilities | Trintech

Variance analysis should be performed regularly to uncover areas of potential fraud, misstatement, or high spending. ... Variance analysis should be performed regularly to uncover areas of potential fraud, misstatement, or high spending. ...
more infohttps://www.trintech.com/brochure/variance-analysis-capabilities/

Variance, Analysis Of | SpringerLinkVariance, Analysis Of | SpringerLink

Analysis of variance (ANOVA) is a statistical procedure for summarizing a classical linear model - a decomposition of sum of ... Variance, Analysis Of, Table 1. Classical two-way analysis of variance for data on five treatments and eight airports with no ... Analysis of variance: Why it is more important than ever (with discussion). Annals of Statistics 33: 1-53.CrossRefGoogle ... Analysis of variance (ANOVA) represents a set of models that can be fit to data, and also a set of methods for summarizing an ...
more infohttps://link.springer.com/referenceworkentry/10.1057/978-1-349-95189-5_2402

Least Squares Predictions and Mean-Variance Analysis by Enrique Sentana :: SSRNLeast Squares Predictions and Mean-Variance Analysis by Enrique Sentana :: SSRN

Least Squares Predictions and Mean-Variance Analysis Journal of Financial Econometrics, Vol. 3, No. 1, pp. 56-78, 2005 ... Sentana, Enrique, Least Squares Predictions and Mean-Variance Analysis. CEMFI Working Paper 9711. Available at SSRN: https:// ...
more infohttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=57848

variance analysisvariance analysis

Tag Archives: variance analysis. Best Practices for Baselining and Variance Analysis. Project Management Institute (PMI)® ... Tags: baselining, Best Practices, Microsoft Project, plan, progress, schedule baseline, scheduling, tracking, variance analysis ...
more infohttps://www.mpug.com/tag/variance-analysis/

Variance Analysis Advantages & DisadvantagesVariance Analysis Advantages & Disadvantages

We all do reports with variance analysis. What do you find as the disadvantage of this type of financial analysis? ... Too often variance analysis becomes a backward looking exercise in "wish I had a crystal ball back then" as we ponder various ... However, in my book variance analysis is the starting point for all performance management. . ... the advantages of variance analysis can outweigh the disadvantages, but only if the conscious choice is to pragmatically focus ...
more infohttps://www.proformative.com/questions/variance-analysis-disadvantages

Fundamentals and Concepts - Standard Costing and Variance Analysis | CourseraFundamentals and Concepts - Standard Costing and Variance Analysis | Coursera

Understand how upper management uses variance analysis • Calculate, interpret, and investigate variances • Understand ... Standard Costing and Variance Analysis. After establishing goals, setting targets, and the budget, upper management uses ... In this module, you will learn how upper management uses variance analysis to motivate and monitor managers and employees, how ... to perform variance analysis on any aspect of the organization, and ultimately understand the power of this important tool for ...
more infohttps://www.coursera.org/lecture/managerial-accounting-business-decisions/fundamentals-and-concepts-xz7LO

Analysis of Variance (ANOVA) DefinitionAnalysis of Variance (ANOVA) Definition

... is a statistical analysis tool that separates the total variability found within a data set into two components: random and ... What is Analysis of Variance (ANOVA)? Analysis of variance (ANOVA) is an analysis tool used in statistics that splits an ... Analysis Of Variances (ANOVA). Analysis of variances (ANOVA) is a statistical examination of the differences between all of the ... when Ronald Fisher created the analysis of variance method. ANOVA is also called the Fisher analysis of variance, and it is the ...
more infohttps://www.investopedia.com/terms/a/anova.asp

Definitions and variance analysis 2010 | Yara InternationalDefinitions and variance analysis 2010 | Yara International

Yaras management also uses a variance analysis methodology, developed within the company ("Variance Analysis"), which involves ... Management considers the estimates produced by the Variance Analysis, and the identification of trends based on such analysis, ... Definitions and variance analysis 2010. The fertilizer season in Western Europe referred to in this discussion starts July 1 ... in the condensed consolidated interim statement of income and are referenced in the variance analysis (see below) as "Special ...
more infohttp://yara.com/investor_relations/annual_report_archive/2010/financial_md_a/definitions_and_variance_analysis/

Bravo Baking Standard Costing Variance Analysis SpreadsheetBravo Baking Standard Costing Variance Analysis Spreadsheet

The data (attached) shows standard cost per unit of $5.11 Part a. Compute the material price and quantity variance. Labor ... Bravo Baking Standard Costing Variance Analysis Spreadsheet. Add. Remove. This content was COPIED from BrainMass.com - View the ... Part a. Compute the material price and quantity variance.. Labor efficiency and labor rate variances. ... brainmass.com/business/product-costing/bravo-baking-standard-costing-variance-analysis-spreadsheet-495713 Attachments. *bravo ...
more infohttps://brainmass.com/business/product-costing/bravo-baking-standard-costing-variance-analysis-spreadsheet-495713

Analysis of VarianceAnalysis of Variance

... is the standard statistical technique for modeling a quantitative response variable ... Fit a model using the appropriate function. Analysis of variance models are fit with the S-PLUS function aov. . This example ... The textbook gives examples in Chapter 10 on fitting many statistical models including analysis of variance. The same basic ... Now that the data is all properly stored in a data frame, we are ready to begin the analysis. Any analysis should begin with a ...
more infohttp://www.stat.wisc.edu/~larget/math496/anova.html

OSA | Multireader multicase variance analysis for binary dataOSA | Multireader multicase variance analysis for binary data

We extend MRMC variance analysis to binary data and also to generic study designs in which every reader may not interpret every ... Multireader multicase variance analysis for binary data Brandon D. Gallas, Gene A. Pennello, and Kyle J. Myers ... Relative Components of Variance on the Scores. Performance:. P. C. =. [. 0.96. ,. 0.86. ,. 0.70. ]. Reader:. σ. R. 2. =. [. ... Relative Components of Variance on the Scores. Performance:. P. C. =. [. 0.96. ,. 0.86. ,. 0.70. ]. Reader:. σ. R. 2. =. [. ...
more infohttps://www.osapublishing.org/josaa/abstract.cfm?URI=josaa-24-12-B70

Overview of Mean Variance - Mean-Variance Analysis and CAPM | CourseraOverview of Mean Variance - Mean-Variance Analysis and CAPM | Coursera

their mean and variance. Were going to define something called. mean-variance optimal portfolios or mean-variance efficient ... Mean-Variance Analysis and CAPM. Problem formulation and solution; the efficient frontier; including the risk-free asset; the ... What is the variance associated with the return of this portfolio?. The formula is Sigma i j x i j, x i x j summed from i ... Overview of Mean Variance. To view this video please enable JavaScript, and consider upgrading to a web browser that supports ...
more infohttps://www.coursera.org/lecture/financial-engineering-2/overview-of-mean-variance-qwIYs

A Generalization of the Mean-Variance Analysis by Valeriy Zakamulin, Steen Koekebakker :: SSRNA Generalization of the Mean-Variance Analysis by Valeriy Zakamulin, Steen Koekebakker :: SSRN

Zakamulin, Valeriy and Koekebakker, Steen, A Generalization of the Mean-Variance Analysis (October 28, 2008). Available at SSRN ... Our analysis shows that a decision maker in this framework exhibits three types of aversions: aversion to loss, aversion to ... This "mean-partial moments" utility generalizes not only the mean-variance utility of Tobin and Markowitz, but also the mean- ... Keywords: risk aversion, loss aversion, risk measure, partial moments of distribution, mean-variance utility, quadratic utility ...
more infohttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=1114771

Analysis of variance | Physics ForumsAnalysis of variance | Physics Forums

... and that the population variances are equal.. Whats being tested is whether theres a difference between the variance of the ... and the mean of the variances of the groups (approxmated by the denominator: the within-groups variance estimate). And one only ... But this is an indirect consequence, an inference from a test of variances.. The objects that play the same role as the two ... population variances in the other kind of F-test - the kind of F-test used simply to test variances - are being used in the ...
more infohttps://www.physicsforums.com/threads/analysis-of-variance.521403/

Analysis of variance - FactbitesAnalysis of variance - Factbites

When using analysis of variance, it is a common practice to present the results of the analysis in an analysis of variance ... In the analysis of Variance, the Total variance is subdivided into two independent variances: the variance due to the treatment ... Doing More with Data Analysis : Performing an Analysis of Variance. In this section, you perform an analysis of variance on the ... You can perform a simple one-way analysis of variance, a complex repeated-measures analysis of variance, a factorial analysis ...
more infohttp://www.factbites.com/topics/Analysis-of-variance

Multivariate analysis of variance - WikiversityMultivariate analysis of variance - Wikiversity

Retrieved from "https://en.wikiversity.org/w/index.php?title=Multivariate_analysis_of_variance&oldid=1640539" ...
more infohttps://en.wikiversity.org/wiki/MANOVA

What Is Budget Variance Analysis? | Chron.comWhat Is Budget Variance Analysis? | Chron.com

Budget variance analysis addresses these differences and helps ... ... What Is Budget Variance Analysis?. by Bert Markgraf Variance analysis helps improve budget accuracy. ... smallbusiness.chron.com/budget-variance-analysis-60250.html Markgraf, Bert. "What Is Budget Variance Analysis?" accessed April ... Standard Cost Variance Calculations and Analysis. *New Jersey Institute of Technology: Cost Management Using Variance Analysis ...
more infohttp://smallbusiness.chron.com/budget-variance-analysis-60250.html

Analysis of Variance DesignsAnalysis of Variance Designs

... Prerequisites. Introduction to ANOVA Learning Objectives. *Be able to identify the factors and ...
more infohttp://onlinestatbook.com/chapter13/anova_designsC.html

Analysis of variance - WikipediaAnalysis of variance - Wikipedia

His first application of the analysis of variance was published in 1921.[10] Analysis of variance became widely known after ... Textbook analysis using a normal distributionEdit. The analysis of variance can be presented in terms of a linear model, which ... variance within treatments. {\displaystyle F={\frac {\text{variance between treatments}}{\text{variance within treatments}}}}. ... Associated analysisEdit. Some analysis is required in support of the design of the experiment while other analysis is performed ...
more infohttps://en.m.wikipedia.org/wiki/ANOVA
  • The analysis is broken down into "sums of squares" that measure the variability due to the levels and due to the errors. (factbites.com)
  • I believe that as a starting point for asking questions as the answers may relate to the future, the advantages of variance analysis can outweigh the disadvantages, but only if the conscious choice is to pragmatically focus on the future and apply the data learned. (proformative.com)
  • In addition, a concise introduction to the principles of analysis of variance and covariance is provided, alongside worked examples illustrating issues and decisions faced by analysts. (cambridge.org)
  • After establishing goals, setting targets, and the budget, upper management uses variance analysis to compare, assess, and investigate differences between actual and expected performance. (coursera.org)
  • Through multiple simulation configurations, we compare our unbiased variance estimates to naïve estimates across a range of study designs, average percent correct, and numbers of readers and cases. (osapublishing.org)
  • The fixed-effects model of analysis of variance applies to situations in which the experimenter has subjected his experimental material to several treatments, each of which affects only the mean of the underlying normal distribution of the "response variable" . (factbites.com)
  • Computes a confidence interval on a variance component estimated as proportional to the difference in two mean squares in a balanced complete experimental design. (roguewave.com)
  • Each of the variance estimates consists of two parts - the sum of squares (SSB and SSW) and degrees of freedom (df). (wisegeek.com)
  • Analysis of variance allows us to investigate if all the graders have the same mean. (factbites.com)
  • Our analysis shows that a decision maker in this framework exhibits three types of aversions: aversion to loss, aversion to uncertainty in gains, and aversion to uncertainty in losses. (ssrn.com)
  • Analysis of variance for testing for the equality of k mean values is a special case of a set of techniques known as linear modeling, which also includes regression analysis , a future topic. (factbites.com)
  • Reasoning is identical to t-tests, only analysis of variance includes independent variables of two or more samples. (wisegeek.com)
  • When using analysis of variance , it is a common practice to present the results of the analysis in an analysis of variance table. (factbites.com)
  • Variance results from cost or price changes and from volume changes. (chron.com)
  • In this module, you will learn how upper management uses variance analysis to motivate and monitor managers and employees, how to perform variance analysis on any aspect of the organization, and ultimately understand the power of this important tool for planning and control. (coursera.org)
  • CFO has featured Conine and his work in two articles on such programs, at Dell and Stanley, Black & Decker , and in Conine-authored pieces on variance analysis , whether to cut volume or price , shareholder return , and, most recently, foreign exchange . (cfo.com)
  • When looking at the difference between estimated cost and actual cost or reconciling the differences in net operating income under variable costing and absorption costing, I'm a big fan of studying the positive variance as it may relate to the future. (proformative.com)
  • The total sum of squares - that is, \( {\sum}_{i=1}^5{\sum}_{j=1}^8{\left({y}_{ij}-\overline{y}..\right)}^2 \) - is 0.078 + 3.944 + 1.417, which can be decomposed into these three terms corresponding to variance described by treatment, variance described by airport, and residuals. (springer.com)
  • Reasons for variance can include changes in sales, changes in material cost or changes in labor cost. (chron.com)
  • This is an authoritatively written book aimed at people who already have a good grasp of analysis of (co)variance using fixed factor an(c)ova, who are not afraid of algebraic notation and who wish to understand the background to the comprehensive range of study designs described which incorporate covariates and random factors. (cambridge.org)