Among the results of a multiple regression analysis are the following sum-of-squares terms: SST, SSR, and SSE. What does each term represent, and how do the terms contribute to our understanding of the relationship between y and the set of independent variables
SST is the total variation in the y values, SSR is the variation in the y values that is explained by the regression, and SSE is the variation in the y values that is not explained by the regression. The coefficient of multiple determination is equal to 1 - (SSE/SST), or SSR/SST. If SSE is small compared to SST, SSR will be large compared to SST, and the multiple regression equation will explain a large portion of the variation in y. Recall that SST = SSR + SSE.
You might also like to view...
The effective interest rate for a discount loan is greater than the loan's stated interest rate
Indicate whether the statement is true or false
The following condensed balance sheet is presented for the partnership of Dunn, Lott, and Tyler who share profits and losses in the ratio of 7:2:1, respectively. Cash$30,000 Other assets 150,000 $180,000 Liabilities$60,000 Dunn, Capital 50,000 Lott, Capital 40,000 Tyler, Capital 30,000 $180,000 The partners agreed that the partnership would be liquidated after selling the other assets. All partners are personally insolvent. What would each of the partners receive if the other assets are sold for $70,000? Dunn Lott TylerA$6,000 $24,000 $22,000 B$0 $21,000 $19,000 C$50,000 $40,000 $30,000 D$0 $20,000 $20,000
A. Option A B. Option B C. Option C D. Option D
The size of a sample is denoted by the letter ____________________ and the size of a population is denoted by the letter ____________________
Fill in the blank(s) with correct word
An important generalization of the Bernoulli distribution concerns the case where a random experiment with infinite outcomes is repeatedly independent
Indicate whether the statement is true or false