• ###### equal probabilities
• The simplest and oldest rule for determining a non-informative prior is the principle of indifference , which assigns equal probabilities to all possibilities. (wikipedia.org)
• For example, the probability of drawing five cards of any one suit is the sum of four equal probabilities, and four times as likely. (gsu.edu)
• ###### rules of probability
• This course introduces the basic ideas and rules of probability, together with some simple probabilistic models and techniques for computing the probabilities of events. (le.ac.uk)
• ###### statistical inference
• In Bayesian statistical inference , a prior probability distribution , often simply called the prior , of an uncertain quantity is the probability distribution that would express one's beliefs about this quantity before some evidence is taken into account. (wikipedia.org)
• ###### true probability
• Quota sampling ensures that you get at least some respondents from all the subpopulations you're interested in, even though this still isn't a true probability sample. (surveymonkey.com)
• If done well, non-probability sampling can give you the same (or better) high-quality data you would expect from a true probability sample. (surveymonkey.com)
• ###### basic probability
• The first section provides a brief description of some of the basic probability concepts that will be used in the activities. (cornell.edu)
• ###### principle of indiffere
• In the classical interpretation, probability was defined in terms of the principle of indifference , based on the natural symmetry of a problem, so, e.g. the probabilities of dice games arise from the natural symmetric 6-sidedness of the cube. (wikipedia.org)
• ###### describes
• A probability distribution is a statistical function that describes possible values and likelihoods that a random variable can take within a given range. (investopedia.com)
• Perhaps the most widely used distribution function in classical physics is the Boltzmann distribution function, which describes the probability of finding particles with an amount of energy E at a given temperature T. (gsu.edu)
• continuous distribution describes events over a continuous range, where the probability of a specific outcome is zero. (mcgill.ca)
• A smooth function that describes the probability of landing anywhere on the dartboard is the probability distribution of the dart throwing event. (mcgill.ca)
• David Hume, the renowned philosopher in his Treatise of Human Nature , describes probability as the amount of evidence that accompanies uncertainty, a reasoning from conjecture. (springer.com)
• ###### finite
• If you allow the outcome x to take a continuous range of values, then the probability P(x) takes a different character, since to get a finite result for probability, you must sum the probability over a finite range of x. (gsu.edu)
• ###### calculus
• But if the number of events is very large, as in the distribution of energy among the molecules of a gas, then the probability can be approximated by a continuous variable so that the methods of calculus can be used. (gsu.edu)
• Our degrees of belief ought to conform to the probability calculus just because the physical chances of the coin tosses conform to that same calculus. (pitt.edu)
• ###### theoretical
• Sometimes we can make mathemitical assumptions about a situation and use Four Basic Properties of Probability to determine the theoretical probability of an event. (calvin.edu)
• The accuracy of a theoretical probability depends on the validity of the mathematical assumptions made. (calvin.edu)
• ###### outcome
• Subjective probability is a type of probability derived from an individual's personal judgment or own experience about whether a specific outcome is likely to occur. (investopedia.com)
• The probability for a given event can be thought of as the ratio of the number of ways that event can happen divided by the number of ways that any possible outcome could happen. (gsu.edu)
• ###### defines
• it defines an event's probability as the limit of its relative frequency in a large number of trials. (wikipedia.org)
• A random variable then defines a probability measure on the sample space by assigning a subset of the sample space the probability of its inverse image in the state space. (mcgill.ca)
• ###### occur
• Subjective probability can be contrasted with objective probability , which is the computed probability that an event will occur based on an analysis in which each measure is based on a recorded observation or a long history of collected data. (investopedia.com)
• Objective probability is the probability that an event will occur based on an analysis in which each measurement is based on a recorded observation. (investopedia.com)
• If you want the probabability that any one of a number of disjoint events will occur, the probabilities of the single events can be added. (gsu.edu)
• In addition, we will use the term personal probability for a statement of someone's degree of belief that an event will occur. (calvin.edu)
• ###### Gaussian
• The simplest probability model is the Gaussian, or normal, distribution, of which there are many examples in biology, medicine, and public health . (encyclopedia.com)
• ###### equally
• One especially important use of these probability rules is the conclusions that can be drawn if we assume that a number of events are equally likely. (calvin.edu)
• If there are only n such events that are possible in a given situation, and all are equally likely and pairwise mutually exclusive (no two can happen at once), then each must have probability 1/ n . (calvin.edu)
• ###### distribution
• For example, the prior could be the probability distribution representing the relative proportions of voters who will vote for a particular politician in a future election. (wikipedia.org)
• For application of probability to physical processes, the use of the distribution function is a very useful strategy. (gsu.edu)
• For any segment of the real line, you can determine exactly what the probability will be that a point will fall on it--even though the distribution extends forever. (mail-archive.com)
• The fact that there's an infinite number of choices doesn't mean that those choices can't be normalized to a probability distribution. (mail-archive.com)
• See also conditional probability and conditional probability distribution . (wikipedia.org)
• push forward measure of the probability distribution on the state space. (mcgill.ca)
• The support of a distribution is the smallest closed set whose complement has probability zero. (mcgill.ca)
• Probability distribution fitting or simply distribution fitting is the fitting of a probability distribution to a series of data concerning the repeated measurement of a variable phenomenon. (wikipedia.org)
• The aim of distribution fitting is to predict the probability or to forecast the frequency of occurrence of the magnitude of the phenomenon in a certain interval. (wikipedia.org)
• Regression method , using a transformation of the cumulative distribution function so that a linear relation is found between the cumulative probability and the values of the data, which may also need to be transformed, depending on the selected probability distribution. (wikipedia.org)
• We will also introduce random variables together with its probability distribution, expectation and variance. (le.ac.uk)
• ###### given
• As it relates to insurance, underwriters may wish to know, for example, if both members of a married couple will reach the age of 75, given their independent probabilities. (investopedia.com)
• vanishingly small, but it has some probability of landing within a given area. (mcgill.ca)
• Empirical probabilities will also follow these rules (for a given set of trials). (calvin.edu)
• ###### example
• An example of subjective probability is a 'gut instinct' when making a trade. (investopedia.com)
• An example of subjective probability is asking New York Yankees fans, before the baseball season starts, about the chances of New York winning the World Series . (investopedia.com)
• Joseph Bertrand introduced it in his work Calcul des probabilités (1889) as an example to show that probabilities may not be well defined if the mechanism or method that produces the random variable is not clearly defined. (wikipedia.org)
• This example is developed in Section 8.3 of " Probability Disassembled " and in " Induction without Probabilities . (pitt.edu)