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This chapter extends to the multivariate context our discussions of ordinary least squares (OLS) regression in the Chapter 6. We first address the logic of multiple regression. We next cover the interpretation of the multiple regression coefficient intercept and slopes, paying particularly close attention to the interpretation of the b slopes. We then address model fit in the multivariate context and extend our discussions of the F-test and the coefficient of multiple determination (R2) by including the standard error of estimate and the Bayesian information criterion (BIC).
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