16. Video: How to Interpret the Results?

We can perform hypothesis tests for the coefficients in our linear models using Python (and other software). These tests help us determine if there is a statistically significant linear relationship between a particular variable and the response. The hypothesis test for the intercept isn't useful in most cases.

However, the hypothesis test for each x-variable is a test of if that population slope is equal to zero vs. an alternative where the parameter differs from zero. Therefore, if the slope is different than zero (the alternative is true), we have evidence that the x-variable attached to that coefficient has a statistically significant linear relationship with the response. This in turn suggests that the x-variable should help us in predicting the response (or at least be better than not having it in the model).