MindTap Business Statistics, 1 term (6 months) Printed Access Card for Anderson/Sweeney/Williams/Camm/Cochran's Essentials of Statistics for Business and Economics, 8th
8th Edition
ISBN: 9781337114288
Author: Anderson, David R.; Sweeney, Dennis J.; Williams, Thomas A.; Camm, Jeffrey D.; Cochran, James J.
Publisher: Cengage Learning
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Chapter 15, Problem 52SE
a.
To determine
Find the missing entries in this output.
b.
To determine
Perform F test to see whether a significant relationship is present at
c.
To determine
Perform t-test to test
d.
To determine
Explain whether the estimated regression equation provides a good fit of the data.
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The admissions officer for a certain college developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and high school GPA.
ŷ = −1.39 + 0.0234x1 + 0.00482x2
where
x1
=
high-school grade point average
x2
=
SAT mathematics score
y
=
final college grade point average.
#1)A high-school average 84 corresponds to x1 = 84
and a score of 535 on the SAT mathematics test corresponds to
x2 = 535. Substitute these values into the estimated regression equation to find the final college GPA, rounding the result to two decimal places.
GPA
=
−1.39 + 0.0234x1 + 0.00482x2
=
-1.39 +0.0234 (_____________) + 0.00482 (535)
=
__________________
The director of marketing at Vanguard Corporation believes that sales of the company's Bright Side laundry detergent (S) are related to Vanguard's own advertising expenditure (A), as well as the combined advertising expenditures of its three biggest rival detergent (R). The marketing director collects 36 weekly observations on S, A and R to estimate the following multiple regression equation:
S = a + bA + cR .where, S, A, and R are measured in dollars per week. Vanguard's marketing director is comfortable using parameter estimates that are statistically significant at the 10% level or better.DEPENDENT VARIABLE: S R-SQUARE F-RATIO P-VALUE ON FOBSERVATIONS: 36 0.2247 4.781 0.0150VARIABLE PARAMETER STANDARD T-RATIO P-VALUE ESTIMATE ERRORINTERCEPT 175086.0 63821.0 2.74 0.0098A 0.8550 0.3250…
The director of marketing at Vanguard Corporation believes that sales of the company’s Bright Side laundry detergent (S) are related to Vanguard’s own advertising expenditure (A), as well as the combined advertising expenditures of its three biggest rival detergents (R). The marketing director collects 36 weekly observations on S, A, and R to estimate the following multiple regression equation: S = a + bA + cR.
where S, A, and R are measured in dollars per week. Vanguard’s marketing director is comfortable using parameter estimates that are statistically significant at the 10 percent level or better.
What sign does the marketing director expect a, b, and c to have?
Interpret the coefficients a, b, and c.
The regression output from the computer is as follows:
3- Does Vanguard’s advertising expenditure have a statistically significant effect on the sales of Bright Side detergent? Explain, using the appropriate p-value.
4- Does advertising by its three largest rivals affect sales of…
Chapter 15 Solutions
MindTap Business Statistics, 1 term (6 months) Printed Access Card for Anderson/Sweeney/Williams/Camm/Cochran's Essentials of Statistics for Business and Economics, 8th
Ch. 15.2 - The estimated regression equation for a model...Ch. 15.2 - Prob. 2ECh. 15.2 - 3. In a regression analysis involving 30...Ch. 15.2 - A shoe store developed the following estimated...Ch. 15.2 - Prob. 5ECh. 15.2 - NFL Winning Percentage. The National Football...Ch. 15.2 - Rating Computer Monitors. PC Magazine provided...Ch. 15.2 - Scoring Cruise Ships. The Condé Nast Traveler Gold...Ch. 15.2 - Prob. 9ECh. 15.2 - Baseball Pitcher Performance. Major League...
Ch. 15.3 - In exercise 1, the following estimated regression...Ch. 15.3 - Prob. 12ECh. 15.3 - 13. In exercise 3, the following estimated...Ch. 15.3 - In exercise 4, the following estimated regression...Ch. 15.3 - Prob. 15ECh. 15.3 - 16. In exercise 6, data were given on the average...Ch. 15.3 - Prob. 17ECh. 15.3 - R2 in Predicting Baseball Pitcher Performance....Ch. 15.5 - In exercise 1, the following estimated regression...Ch. 15.5 - Prob. 20ECh. 15.5 - The following estimated regression equation was...Ch. 15.5 - Testing Significance in Shoe Sales Prediction. In...Ch. 15.5 - Testing Significance in Theater Revenue. Refer to...Ch. 15.5 - Testing Significance in Predicting NFL Wins. The...Ch. 15.5 - Prob. 25ECh. 15.5 - Testing Significance in Baseball Pitcher...Ch. 15.6 - In exercise 1, the following estimated regression...Ch. 15.6 - Prob. 28ECh. 15.6 - Prob. 29ECh. 15.6 - Prob. 31ECh. 15.7 - Consider a regression study involving a dependent...Ch. 15.7 - Consider a regression study involving a dependent...Ch. 15.7 - 34. Management proposed the following regression...Ch. 15.7 - Repair Time. Refer to the Johnson Filtration...Ch. 15.7 - Extending Model for Repair Time. This problem is...Ch. 15.7 - 37. The Consumer Reports Restaurant Customer...Ch. 15.9 - In Table 15.12 we provided estimates of the...Ch. 15 - 49. The admissions officer for Clearwater College...Ch. 15 - 50. The personnel director for Electronics...Ch. 15 - Prob. 51SECh. 15 - Prob. 52SECh. 15 - Recall that in exercise 50 the personnel director...Ch. 15 - Analyzing Repeat Purchases. The Tire Rack,...Ch. 15 - Prob. 55SECh. 15 - Mutual Fund Returns. A portion of a data set...Ch. 15 - Prob. 57SECh. 15 - Consumer Research, Inc., is an independent agency...Ch. 15 - Matt Kenseth won the 2012 Daytona 500, the most...Ch. 15 - When trying to decide what car to buy, real value...
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- The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.arrow_forwardOlympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardThe director of marketing at Vanguard Corporation believes that sales of the company's Bright Side laundry detergent (S) are related to Vanguard's own advertising expenditure (A), as well as the combined advertising expenditures of its three biggest rival detergents (R). The marketing director collects 36 weekly observations on S, A, and R to estimate the following multiple regression equation: S = a + bA + cR where S, A, and R are measured in dollars per week. Vanguard's marketing director is comfortable using parameter estimates that are statistically significant at the 10 percent level or better. a. What sign does the marketing director expect a, b, and c to have? b. Interpret the coefficeints a, b, and c. The regression output from the computer is as follows: c. Does Vanguard's advertising expenditure have a statistically significant effect on the sales of Bright Side detergent? Explain, using the appropriate…arrow_forward
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