You cannot simply look at the results of the tests for normality to decide if a parametric test is valid or not. This is the point where many people make a mistake. Should you abandon the t-test results and run a nonparametric test analysis such as a Wilcoxon Rank Sum test that does not require normal distributions? On the OPTIONS tab, check the box for Tests for normality as shown below.Īll the tests for normality for both 4-cylinder and 6-cylinder cars reject the null hypothesis that the data values come from a population that is normally distributed. Use a filter to include only 4- or 6-cylinder cars. Next request a Two-sample test, with Horsepower as the Analysis variable and Cylinders as the Groups variable. On the DATA tab, select the Cars data set in the SASHELP library. Tasks and Utilities → Tasks → Statistics → t Tests There are several SAS Studio tasks that include options to test this assumption. The procedure that calculates the test statistic compares your data to what is expected under the null hypothesis. When we assume a normal distribution exists, we can identify the probability of a particular outcome. With all inferential statistics, we assume the dependent variable fits a normal distribution. It is used to determine whether there is a significant difference between the means of two groups. A test statistic is a standardized value that is calculated from sample data during a hypothesis test. T-values are an example of what statisticians call test statistics.
T-tests are called t-tests because the test results are all based on t-values. The t-test is a very useful test that compares one variable (perhaps blood pressure) between two groups.