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TABLE 13-8It is believed that GPA (grade point average, based on a four point scale) should have a positive linear relationship with ACT scores. Given below is the Excel output from regressing GPA on ACT scores using a data set of 8 randomly chosen students from a Big-Ten university.  Regressing GPA on ACT   ANOVA  Referring to Table 13-8, what is the predicted average value of GPA when ACT = 20?

Test H0: β = 1 vs. H1: β < 1 if the following regression information are given: b1 = 1.39,  sb1= 0.18, and n = 30.

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:The manager of a used-car dealership is very interested in the resale price of used cars. The manager feels that the age of the car is important in determining the resale value. He collects data on the age and resale value of 15 cars and runs a regression analysis with the value of the car (in thousands of dollars) as the dependent variable and the age of the car (in years) as the independent variable. Unfortunately, he spilled his coffee on the printout and lost some of the results, identified by “A” through “F”. The partial results left are displayed below.What is the value of *E*?

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:An insurance company analyst is interested in analyzing the dollar value of damage in automobile accidents. She collects data from 115 accidents, and records the amount of damage as well as the age of the driver. The results of her regression analysis are listed below.How would you best explain the y-intercept in this situation?

For a two-tailed test of significance of slope coefficient (β1), the appropriate null hypothesisis most likely to be:

TABLE 13-10The management of a chain electronic store would like to develop a model for predicting the weekly sales (in thousand of dollars) for individual stores based on the number of customers who made purchases. A random sample of 12 stores yields the following results: CustomersSales (Thousands of Dollars)90711.2092611.057138.217419.217809.4289810.085106.735297.024606.128729.526507.536037.25Referring to Table 13-10, which is the correct null hypothesis for testing whether the number of customers who make purchase affects weekly sales?

TABLE 13-9It is believed that, the average numbers of hours spent studying per day (HOURS) during undergraduate education should have a positive linear relationship with the starting salary (SALARY, measured in thousands of dollars per month) after graduation. Given below is the Excel output from regressing starting salary on number of hours spent studying per day for a sample of 51 students. NOTE: Some of the numbers in the output are purposely erased.   ANOVA  Referring to Table 13-9, the 90% confidence interval for the average change in SALARY (in thousands of dollars) as a result of spending an extra hour per day studying is

TABLE 13-8It is believed that GPA (grade point average, based on a four point scale) should have a positive linear relationship with ACT scores. Given below is the Excel output from regressing GPA on ACT scores using a data set of 8 randomly chosen students from a Big-Ten university.  Regressing GPA on ACT   ANOVA  Referring to Table 13-8, the value of the measured test statistic to test whether there is any linear relationship between GPA and ACT is

The set of the input values of a function is called the:

TABLE 13-2A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below:   SUMMARY OUTPUT Regression Statistics Multiple R 0.885404 R Square 0.783941 Adjusted R Square 0.729926 Standard Error 16.29861 Observations 6 ANOVA   df SS MS F Significance F Regression 1 3855.422 3855.422 14.51346 0.018946 Residual 4 1062.578 265.6446 Total 5 4918         Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 161.3855 26.16069 6.16901 0.003506 88.75183 234.0193 88.75183 234.0193 price -48.1928 12.65017 -3.80965 0.018946 -83.3153 -13.0703 -83.3153 -13.0703 Referring to the above Table, what is the standard error of the regression slope estimate, Sb1?