 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: ... 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. ... Harry Markowitz
ISBN 978-0-8247-2263-0. Markowitz, H.M. and E. van Dijk (March-April 2003). "Single-Period Mean-Variance Analysis in a Changing ... 5. Analysis is based on single period model of investment. 6. An investor either maximizes his portfolio return for a given ... The HM model is also called mean-variance model due to the fact that it is based on expected returns (mean) and the standard ... Mean-variance optimization has been dubbed an 'error maximization' device (Scherer 2002): 'an algorithm that takes point ... Scheffé's method
It is particularly useful in analysis of variance (a special case of regression analysis), and in constructing simultaneous ... Scheffé, H. (1999) . 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 ... 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).  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 ... Uncertainty quantification
The targets of uncertainty propagation analysis can be: To evaluate low-order moments of the outputs, i.e. mean and variance. ... Modularization in Bayesian Analysis, with Emphasis on Analysis of Computer Models, Bayesian Analysis (2009) 4, Number 1, pp. ... In regression analysis and least squares problems, the standard error of parameter estimates is readily available, which can be ... The probabilistic approach is considered as the most rigorous approach to uncertainty analysis in engineering design due to its ...