BUS 215 Lecture Notes - Lecture 13: F-Test, Used Cars, Test Statistic
4 Apr 2016
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Document Summary
The partial f test is designed to answer questions such as these by comparing two linear models for the same response variable. The extra sum of squares is used to measure the marginal increase in the error sum of squares when one or more predictors are deleted from a model. Conversely, the extra sum of squares measures the marginal reduction in the error sum of squares when one or more predictors are added to a model. Y = 0 + 1x1 + 2x2 + + kxk. We will start by showing how to assess the effect of eliminating some predictors from a model that contains k predictors. The model containing all the predictors is called the full model: (13a. 1) A model with fewer predictors is a reduced model. We estimate the linear regression for each of the two models, and then look at the error sum of squares (sse) from the anova table for each model.
