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 includes drawing a stem-and-leaf plot, scatterplot, box-plot, histogram, probability-probability (P-P) plot, and quantile-quantile (Q-Q) plot. The latter computes 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 information 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 February 11, 2009.
