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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.
Nested design is the design in which levels of one or more factors are subsampled within one or more other factors such that, for instance, each level of a factor B happens at onl
Biplots: It is the multivariate analogue of the scatter plots, which estimates the multivariate distribution of the sample in a few dimensions, typically two and superimpose on th
Human height growth curves : The growth of human height is, in common, remarkably regular, apart from the pubertal growth spurt. The satisfactory longitudinal development curve is
distinguish the historigram and histogram
Generalized method of moments (gmm) is the estimation method popular in econometrics which generalizes the method of the moments estimator. Essentially same as what is known as the
Write a c++ program to find the sum of 0.123 ? 103 and 0.456 ? 102 and write the result in three significant digits
The graphical method for studying the behavior of the seasonal time series. In such a plot, the January values of seasonal component are graphed for the upcoming years, then the
Multiple comparison tests : Procedures for detailed examination of the differences between a set of means, generally after a general hypothesis that they are all equal has been rej
Lancaster models : The means of representing the joint distribution of the set of variables in terms of the marginal distributions, supposing all the interactions higher than a par
Discuss the use of dummy variables in both multiple linear regression and non-linear regression. Give examples if possible
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