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Normality - Reasons for Screening Data
Prior to analyzing multivariate normality, one should consider univariate normality
Multivariate normality refers to a normal distribution of combination of variables (two-by-two, plus all linear combination of the variables) Univariate normality is a necessary but not sufficient condition for multivariate normality.
For bivariate normality one should check all the two-by-two scatter plots (they should have elliptical shape)
Sometimes data transformation is necessary for normality.
The procedure in which initially the sample of subjects is selected for generating the auxillary information only, and then the second sample is selected in which the variable of i
Normality - Reasons for Screening Data Prior to analyzing multivariate normality, one should consider univariate normality Histogram, Normal Q-Qplot (values on x axis
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Principal components analysis is a process for analysing multivariate data which transforms original variables into the new ones which are uncorrelated and account for decreasing
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