One of the major assumptions of Linear Regression is that there should be no autocorrelation of the residuals.
Autocorrelation occurs when the residuals are not independent from each other. In other words when the value of y(t+1) is not independent from the value of y(t).
To check for autocorrelation, we can use the Durbin-Watson statistic to detect the presence of autocorrelation at lag 1 in the residuals from a regression analysis.
So, In this video, I’ll define the Hypothesis for the Durbin-Watson Statistic along & also show you how it can be implemented from scratch.