Now that we've explored correlation we'll take a brief look at using the "linear model" function lm() to fit regressions. We'll also look at how we can examine the residuals (stored inside the "lm object" created by lm()) to see if their distribution is approximagely normal. Note that we'll we explore regression in much more detail in a later chapter.