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Generalized principal components analysis: The non-linear version of the principal components analysis in which the goal is to determine the non-linear coordinate system which is most in agreement with the data configuration. For instance, for the bivariate data, y1,y2, if the quadratic coordinate system is sought, a variable z is defined as given below: with the coefficients being set up so that the variance of z is a maximum amongst all such quadratic functions of y1 and y2.
The Null Hypothesis - H0: γ 1 = γ 2 = ... = 0 i.e. there is no heteroscedasticity in the model The Alternative Hypothesis - H1: at least one of the γ i 's are not equal
Case-control study : The traditional case-control study is the common research design in the epidemiology where the exposures to risk factors for cases (individuals getting the dis
An approach to investigations designed to recognize a particular medical condition in the large population, usually by means of a blood test, which might result in the considerable
The graphical process most frequently used in the analysis of data from a two-by-two crossover design. For each of the subject the difference between the response variable values o
Attitude scaling : The process of analysing the positions of the individuals on scales purporting to measure attitudes, for instance a liberal-conservative scale, ora risk-willingn
Non central distributions is the series of probability distributions each of which is the adaptation of one of the standard sampling distributions like the chi-squared distributio
The transformation of the Pearson's product moment correlation coefficient, r, can be given by The statistic z has the normal distribution with mean here ρ is the pop
Centile reference charts : Charts which are used inmedicine to observe the clinical measurements on individual patients in the context of the population values. If the population i
Unequal probability sampling is the sampling design in which the different sampling units in the population have different probabilities of being included in sample. The differing
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
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