Perform the one-sample Kolmogorov-Smirnov test by using kstest. Confirm the test decision by visually comparing the empirical cumulative distribution function (cdf) to the standard normal cdf.

Load the examgrades data set. Create a vector containing the first column of the exam grade data.

Test the null hypothesis that the data comes from a normal distribution with a mean of 75 and a standard deviation of 10. Use these parameters to center and scale each element of the data vector, because kstest tests for a standard normal distribution by default.

The returned value of h = 0 indicates that kstest fails to reject the null hypothesis at the default 5% significance level.

Plot the empirical cdf and the standard normal cdf for a visual comparison.

The figure shows the similarity between the empirical cdf of the centered and scaled data vector and the cdf of the standard normal distribution.