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Probability distribution: For the discrete random variable, a mathematical formula which provides the probability of each value of variable. See, for instance, binomial distribution and Poisson distribution. For the continuous random variable, a curve described by the mathematical formula which specifies, by way of area under the curve, the probability which the variable falls within the particular interval. Examples comprise the normal distribution and the exponential distribution. In both the cases the term probability density might also be used. (A distinction is sometimes made among 'density' and 'distribution', when the latter is reserved for probability that the random variable comes below some value. In this dictionary, though, the latter will be termed the cumulative probability distribution and the probability distribution and probability density both are used synonymously.
Introduction to Generalized Linear Models (GLM) We introduce the notion of GLM as an extension of the traditional normal-theory-based linear regression models. This will be very
It is used generally for the matrix which specifies a statistical model for a set of observations. For instance, in a one-way design with the three observations in one group, tw
Indirect least squares: An estimation technique used in the fitting of structural equation models. Commonly least squares are first used to estimate reduced form parameters. Usi
Length-biased data is a data which arise when the probability that an item is sampled is proportional to its own length. A main example of this situation occurs in the renewal the
A procedure whereby the collection of multiple sample units are combined in their entirety or in part, to form the new sample. One or more succeeding measurements are taken on the
Bayesian network : It is essentially an expert system in which the uncertainty is dealt with using the conditional probabilities and Bayes' Theorem. Formally such type of network c
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Multivariate data is the data for which each observation consists of the values for more than one random variable. For instance, measurements on the blood pressure, temperature an
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A term commonly encountered in the analysis of the contingency tables. Such type of frequencies are the estimates of the values to be expected under hypothesis of interest. In a tw
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