Question

1. In regression analysis, the Sum of Squares Total (SST) is

a. The total variation of the dependent variable

b. The total variation of the independent variable

c.  The variation of the dependent variable that is explained by the regression line

d. The variation of the dependent variable that is unexplained by the regression line

Question 2 In regression analysis, the Sum of Squares Regression (SSR) is
		A.  The total variation of the dependent variable B.  The total variation of the independent variable C.  The variation of the dependent variable that is explained by the regression line D.  The variation of the dependent variable that is unexplained by the regression line

Question 3 In regression analysis, the Sum of Squares Error (SSE) is
		A.  The total variation of the dependent variable B.  The total variation of the independent variable C.  The variation of the dependent variable that is explained by the regression line D.  The variation of the dependent variable that is unexplained by the regression line

Question 4 In regression analysis, which of the following is NOT true?
		A.  The standard error of the estimate is the standard deviation of the data points around the regression line. B.  The total variation in y is the sum of SSR + SSE. C.  R-squared measures the proportion of the variation in y that is explained by the variation in x. D.  A negative R-squared means that y has a negative correlation with x.

You collected data with a sample size of 12 then ran a simple regression and obtained SSR = 341 and SSE = 145.

	5.1.	Question 5.1 What is the R-squared of your regression?
		A.  0.7016 B.  0.8014 C.  0.3512 D.  0.2984

You collected data with a sample size of 12 then ran a simple regression and obtained SSR = 341 and SSE = 145.

	5.2.	Question 5.2 What is the Standard Error of the Estimate?
		A.  1.45 B.  196 C.  3.81 D.  14.5

6.	Question 6 When R-squared is zero, then
		A.  the standard error of the estimate is also zero. B.  there is a perfect match between the regression line and the data points. C.  there is no residual from the regression of y on x. D.  there is no linear relationship between x and y.

7.	Question 7 You have sample data of x and y with the following statistics: The sample covariance of x and y is 35.6. The sample variance of x is 40.7. The sample variance of y is 32.8. What is the value of the R-squared?
		A.  0.821 B.  0.949 C.  0.027 D.  0.051

Answer 1

1)

a. The total variation of the dependent variable

2)

C.  The variation of the dependent variable that is explained by the regression line

3)

D.  The variation of the dependent variable that is unexplained by the regression line

4)

D.  A negative R-squared means that y has a negative correlation with x.

5.1)

R² =341/(341+145)=0.7016

5.2)

Standard Error of the Estimate =sqrt(SSE/(n-2))=sqrt(145/10)=3.81

6)

optionA ,C and D are correct

7)

R-squared =(35.6²/(40.7*32.8))=0.949