Estimate the regression equation and correlation coefficient.
1. The following results were obtained from a simple regression analysis:
= 37.2895-(1.2024)X r2=.6744, Sb1=.2934
For each unit change in X (independent variable), the estimated change in Y (dependent variable) is equal to
a. -1.2024
b. 6744
c. 37.2895
d. 2934
2. The following results were obtained from a simple regression analysis:
= 37.2895-(1.2024)X r2=.6744 Sb1=.2934
When X (independent variable) is equal to zero, the estimated value of Y (dependent variable) is equal to:
a. -1.2024
b. 6744
c. 37.2895
d. 2934
3. The following results were obtained from a simple regression analysis:
= 37.2895-(1.2024)X r2=.6744 Sb1=.2934 ____________ is the proportion of the variation explained by the simple linear regression model:
a. -1.2024
b. .6744
c. 37.2895
d. .2934
4. For the same set of observations on the specified dependent variable two different independent variables were used to develop two separate simple linear regression models. A portion of the results is presented below. Based on the results given above, we can conclude that:
a. A prediction based on Model 1 is better than a prediction based on Model 2
b. A prediction based on Model 2 is better than a prediction based on Model 1
c. There is no difference in the predictive ability between Model 1 and Model 2
d. There is not sufficient information to determine which of the two models is superior for prediction purposes
5. The local grocery store wants to calculate the daily sales in dollars. The manager believes that the amount of newspaper advertising significantly affects the store sales. He randomly selects 7 days of data consisting of daily grocery store sales (in thousands of dollars) and advertising expenditures (in thousands of dollars). The Excel/Mega-Stat output given above summarizes the results of regression model.
What is the estimated simple linear regression equation?
a. 7.9682+1.667 X
b. 63.333+6.667 X
c. 7.948+4.000 X
d. 11.547+1.667 X
e. 6.667+63.333 X