SOC202H1 Lecture Notes - Lecture 11: Linear Regression, Explained Variation, Analysis Of Variance
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Thought question: one equation using priors as x, and another equation based on age as x- then adding together the r2 values. Why is this a bad idea: assuming that they are additive. If you have two strong r values= might have a greater than 1. 00 sum and thus cannot have more than (cid:883)(cid:882)(cid:882)% can be explained variation . Multiple regression helps determine what percentage of variation in the dependent variable is explained for both prior and age, accounting for the fact that the two predictors overlap. From our example, we could calculate a multiple regression equation predicting sentence lengths as follows: For each additional prior, there is an increase in 2. 39 months sentence length holding constant the defendant"s age. Being tested on the interpretation of multiple linear regression and not making a calculation to get to that point. Be able to interpret the information- know what they mean.
