Testing Assumptions II

One of the assumptions for running a regression analysis is that the relationship between the predictor and response variable is linear. It was a little hard to tell if this was definitely the case from plotting money against liking in the last exercise. Let's use those residuals you stored as resmod1 and plot these against liking to see if we can get a better idea of linearity.

While we are looking at these residuals, we can also check out the assumption of homoscedasticity. To check this we should make sure the variation in residuals is roughly even at all levels of the predictor and response variables.

To do this we're going to use the plot() function. The first argument that plot takes is the x axis variable, and the second is the y-axis variable. After this plot() can take many optional arguments, but you don't need to worry about these right now.