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.
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