# How do you test if a variable is normally distributed 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.Click to see full answer. Then, how do you test if a variable is normally distributed?For quick and visual identification of a normal distribution, use a QQ plot if you have only one variable to look at and a Box Plot if you have many. Use a histogram if you need to present your results to a non-statistical public. As a statistical test to confirm your hypothesis, use the Shapiro Wilk test. how do I interpret the Shapiro Wilk test for normality? The Prob < W value listed in the output is the p-value. If the chosen alpha level is 0.05 and the p-value is less than 0.05, then the null hypothesis that the data are normally distributed is rejected. If the p-value is greater than 0.05, then the null hypothesis is not rejected. Also to know, what is skewness and kurtosis test for normality? In statistics, normality tests are used to determine whether a data set is modeled for normal distribution. Statistically, two numerical measures of shape – skewness and excess kurtosis – can be used to test for normality. If skewness is not close to zero, then your data set is not normally distributed.How do I test for normal distribution in SPSS? Performing Normality in PASW (SPSS) Select "Analyze -> Descriptive Statistics -> Explore”. From the list on the left, select the variable “Data” to the “Dependent List”. Click “Plots” on the right. A new window pops out. The test statistics are shown in the third table. Here two tests for normality are run.