Author: sahaymaniceet

Ever wondered why we look for p-value less than 0.05 for the coefficients when looking at the linear regression results.

Let’s quickly recap the basics of linear regression. In Linear Regression we try to estimate a best fit line for given data points. In case we have only one predictor variable and a target the linear equation will look something like

Y = A + Bx

Here A being the intercept and B being the slope or coefficient.

The null hypothesis for linear regression is that B=0 and the alternate hypothesis is that B != 0.

This is the reason why we look for p-value < 0.05 to reject the null hypothesis and establish that there exists a relationship between the target and the predictor variable.