How to perform test of Normality Data with STATA

In Stata, you can test normality by either graphical or numerical methods. The former include drawing a stem-and-leaf plot, scatterplot, box-plot, histogram, probability-probability (P-P) plot, and quantile-quantile (Q-Q) plot. The latter involve computing the Shapiro-Wilk, Shapiro-Francia, and Skewness/Kurtosis tests.
The examples below are for the variable score:
Graphical methods 
CommandPlot drawn
. stem scorestem-and-leaf
. dotplot scorescatterplot
. graph box scorebox-plot
. histogram scorehistogram
. pnorm scoreP-P plot
. qnorm scoreQ-Q plot 
Numerical methods 
CommandTest conducted
. swilk scoreShapiro-Wilk
. sfrancia scoreShapiro-Francia 
. sktest scoreSkewness/Kurtosis
Be aware that in these tests, the null hypothesis states that the variable is normally distributed. That means the data is considered normal if > 0.05
good luck

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