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.
For more about statistical and mathematical software, email the UITS Stat/Math Center, visit the center's web page, or phone 812-855-4724 (IUB) or 317-278-4740 (IUPUI). The center is located in Bloomington at 410 N. Park Avenue, and is open for consultation by appointment Monday-Friday 9am-5pm.
Last modified on May 26, 2011.
