Categorical predictors (comparing means)

In this lecture we look at how to incorporate categorical predictors (group membership) into a linear model to compare the means of those categories/groups. We look at using dummy/indicator coding to compare means of two groups, then extend the example to look at 3 groups. We see that the parameter estimates (b) represent differences between group means. We also see that the overall model fit is assessed with the F-statistic, which is calculated in the same way as for models with continuous predictors.


Learn R alongside these lectures with the discovr package (https://www.discovr.rocks/discovr/)


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