# Test the normality of a variable in 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 | |
---|---|

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 the UITS Research Applications and Deep Learning team.

## Related documents

*This is document* alug *in the Knowledge Base.*

*Last modified on* 2019-01-31 15:41:34*.*