Normality tests are tests of whether a set of data is distributed in a way that is consistent with a normal distribution. Typically, they are tests of a null hypothesis that the data are drawn from a normal population, specifically a goodness-of-fit test. Hence, while it is possible to reach a definitive conclusion that a set of data is not normally-distributed (by rejecting the null hypothesis), the most one can say if the null hypothesis is not rejected is that the data could possibly come from a normally distributed population. See Lilliefors test for normality.
Browse Other Glossary Entries
Planning on taking an introductory statistics course, but not sure if you need to start at the beginning? Review the course description for each of our introductory statistics courses and estimate which best matches your level, then take the self test for that course. If you get all or almost all the questions correct, move on and take the next test.
Find the right course for you
We'd love to answer your questions
Our mentors and academic advisors are standing by to help guide you towards the courses or program that makes the most sense for you and your goals.
300 W Main St STE 301, Charlottesville, VA 22903