Normality - reasons for screening data, Advanced Statistics

Normality - Reasons for Screening Data

Prior to analyzing multivariate normality, one should consider univariate normality

  • Histogram, Normal Q-Qplot (values on x axis with expected normal values on the y axis)
  • Skewness and Kurtosis (null hypothesis: values around zero with alpha levels of .01 or .001
  • Kolmogorov-Smirnov Test

 

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.

 

Posted Date: 3/4/2013 6:25:28 AM | Location : United States







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