T Test Vs Chi Square. Variable a and variable b are independent. A t test is designed to test a null hypothesis by determining if two sets of data are significantly different from one another while a chi squared test tests the null hypothesis by finding out if there is a relationship between the two sets of data.
In contrast to the chi square values which result from squared differences the residuals are not squared. But it does not tell you the direction or the size of the relationship. Learning statistics doesn t need to be difficult.
The difference is meaningful.
While the chi square test also helps you to find the relationship between two variables but has no direction and size of the relationship. Allows you to test whether or not there is a statistically significant difference between two population means. In contrast to the chi square values which result from squared differences the residuals are not squared. T test for a difference in means.
