Why Do We Use T Test in Regression

Whenever we perform linear regression, we want to know if there is a statistically significant relationship between the predictor variable and the response variable. We test for significance by performing a t-test for the regression slope.

Why is t-test used in regression?

Linear Regression is one of the types of regression analysis which is also a method of inferential statistics. A T-test is used to compare the means of two different sets of observed data and to find to what extent such difference is ‘by chance’.

What is the difference between t-test and regression?

The main difference is that t-tests and ANOVAs involve the use of categorical predictors, while linear regression involves the use of continuous predictors. When we start to recognise whether our data is categorical or continuous, selecting the correct statistical analysis becomes a lot more intuitive.