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The following parts involve ANOVA concepts in general. a) Complete the sentence:

ID: 3224008 • Letter: T

Question

The following parts involve ANOVA concepts in general. a) Complete the sentence: The total sum of squares (SST) is the sum of squared differences between y_i (the _ response) and y (the _ response). b) Complete the sentence: The residual sum of squares (SSE) is the sum of squared differences between y_i (the _ response) and y_i (the _ response); the differences are also called _. c) Complete the sentence: The regression sum of squares (SSR) equals the difference between _ and _. (This is not asking for the difference of which two kinds of values that would be squared, then summed, in order to calculate SSR) d) Complete the sentence: In general, ANOVA performs a hypothesis test for _ at once; for MLR, it tests the _ parameters. e) To calculate mean squares, the corresponding sum of squares is divided by which corresponding value? f) In an ANOVA table, the calculated test statistic comes from an F distribution with two parameters: numerator degrees of freedom (ndf), and denominator degrees of freedom (ddf). If SSR has k df and SST has n - 1 df, what are the ndf and ddf, in terms of k and n? g) Consider using ANOVA to compare a "Full" model to a "Reduced" model. In performing the hypothesis test, which model does the null hypothesis support: the "Full" or "Reduced" one? Briefly explain why. h) If a test from part (g) produces in a small p-value, which model does the test suggest is preferred: the "Full" or "Reduced" one?

Explanation / Answer

These are simply given by definition of these terms used in Linear Regression. Hence, answers DO NOT need long explanations. Here are the answers:

(a) i-th observed, sample mean

(b) i-th observed, theoretically estimated i-th

(c) Sum of Squares due to Errors

(d) comparison of multiple parameters, individual

Answering only (a) to (d) are suffcient as per Chegg policy.