In the accompanying table, we give the smallest SSE for each number of predictors k (k = 1, 2, 3, 4) for a regression problem in which y = cumulative heat of hardening in cement, x1 = % tricalcium aluminate, x2 = % tricalcium silicate, x3 = % aluminum ferrate, and x4 = % dicalcium silicate.

In addition, n = 13 and SST = 2715.76.
a. Use the criteria discussed in the text to recommend the use of a particular regression model.
b. Would forward selection result in the best two predictor model? Explain.

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Number of Predictors k Predictor(s) SSE 880.85 58.01 49.20 47.86 x1. X2 4 xi, t ,x 1- 12 13-