In Stata, how do I test the normality of a variable?

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
Command Plot drawn
. stem score stem-and-leaf
. dotplot score scatterplot
. graph box score box-plot
. histogram score histogram
. pnorm score P-P plot
. qnorm score Q-Q plot
Numerical methods
Command Test conducted
. swilk score Shapiro-Wilk
. sfrancia score Shapiro-Francia
. sktest score Skewness/Kurtosis

Be aware that in these tests, the null hypothesis states that the variable is normally distributed.

If you have questions about using statistical and mathematical software at Indiana University, contact Research Analytics. Research Analytics is located on the IU Bloomington campus at Woodburn Hall 200; staff are available for consultation Monday-Friday 9am-noon and by appointment.

Note:
For details about availability of UITS services during Thanksgiving break, see UITS Thanksgiving break support hours.

This is document alug in the Knowledge Base.
Last modified on 2016-01-19 00:00:00.

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