Unlike t-tests that can assess only one regression coefficient at a time, the F-test can assess multiple coefficients simultaneously. In general, an F-test in regression compares the fits of different linear models. Recently I've been asked, how does the F-test of the overall significance and its P value fit in with these other statistics? That’s the topic of this post! I’ve also written about how to interpret R-squared to assess the strength of the relationship between your model and the response variable. Previously, I’ve written about how to interpret regression coefficients and their individual P values.
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