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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Question
Chapter 15.6, Problem 29E
a.
To determine
Find the gross revenue expected for a week when $3,500 is spent on television advertising (
b.
To determine
Find a 95% confidence interval for the mean revenue of all weeks with the expenditures listed in part (a).
c.
To determine
Find a 95% prediction interval for the next week’s revenue of all weeks with the expenditures listed in part (a).
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In exercise 5, the owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue ( y) as a function of television advertising (x1) and newspaperadvertising (x2). The estimated regression equation wasThe computer solution provided SST = 25.5 and SSR = 23.435.
yˆ = 83.2 + 2.29x1 + 1.30x2
a. Compute and interpret R2 and .b. When television advertising was the only independent variable, R2 + .653 and R2a=.595. Do you prefer the multiple regression results? Explain
Create the regression equations based on the research model below!
An online shopping website collected data regarding its operations and obtained the following linear regression model for the estimated revenue in millions, , based on the click-through rate in thousands, x.
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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- Olympic 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_forwardLife Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?2300arrow_forwardDoes Table 1 represent a linear function? If so, finda linear equation that models the data.arrow_forward
- The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x 1) and newspaper advertising (x 2). The estimated regression equation was Weekly Gross Revenue ($1000s) Televison Advertising ($1000s) Newspaper Advertising ($1000s) 97 6 1.5 91 3 2 95 5 2.5 93 3.5 2.5 96 4 4.3 94 4.5 2.3 95 3.5 4.2 95 4 3.5 ŷ = 82.5 + 2.01 x 1 + 1.26 x 2The computer solution provided SST = 24 and SSR = 22.876. Compute R 2 and R a 2 (to 3 decimals). R 2 R a 2 When television advertising was the only independent variable, R 2 = 0.551 and R a 2 = 0.476. Are the multiple regression analysis results preferable?arrow_forwardWhich of the multivariate regression parameters listed below would be best interpreted as: the predicted value on the dependent variable when all of the independent variables in the model are equal to zero. a b1 X1 R2arrow_forwardA carpenter wanted to predict how many pieces of furniture they could produce in a certain time frame. They calculated a linear regression equation and obtained the following results:Using these results how many pieces can they create in 5 hours? y^=2x+2arrow_forward
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