14. The regression R² is a measure of: whether or not X causes Y. a. b. the goodness of fit of your regression line. c. whether or not ESS> TSS. d. the square root of the correlation coefficient.

ENGR.ECONOMIC ANALYSIS
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Chapter1: Making Economics Decisions
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14. The regression R² is a measure of:
a. whether or not X causes Y.
b. the goodness of fit of your regression line.
c. whether or not ESS> TSS.
d. the square root of the correlation coefficient.
15. The OLS residuals, û, are defined as follows:
a. Ŷ-Bo-B₁X;
R
b. Y – Bo – PıX
c. (Y-Y)²
d. Y₁ - Ŷ,
16. There exist a relationship test scores and the student-teacher ratio can be modeled as a
linear function with an intercept of 798.9 and a slope of -3.28. A increase in the student-
teacher ratio by 2 will:
a. Reduces test scores by 3.28 on average
b.
Results in a test score of 798.9
c. Reduces test scores by 6.56 on average
d.
Reduces test scores by 6.56 for every school district
Transcribed Image Text:14. The regression R² is a measure of: a. whether or not X causes Y. b. the goodness of fit of your regression line. c. whether or not ESS> TSS. d. the square root of the correlation coefficient. 15. The OLS residuals, û, are defined as follows: a. Ŷ-Bo-B₁X; R b. Y – Bo – PıX c. (Y-Y)² d. Y₁ - Ŷ, 16. There exist a relationship test scores and the student-teacher ratio can be modeled as a linear function with an intercept of 798.9 and a slope of -3.28. A increase in the student- teacher ratio by 2 will: a. Reduces test scores by 3.28 on average b. Results in a test score of 798.9 c. Reduces test scores by 6.56 on average d. Reduces test scores by 6.56 for every school district
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