Modern Business Statistics with Microsoft Office Excel (with XLSTAT Education Edition Printed Access Card)
6th Edition
ISBN: 9780357228708
Author: David R. Anderson; Dennis J. Sweeney; Thomas A. Williams
Publisher: Cengage Learning US
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Chapter 15.7, Problem 33E
a.
To determine
Find the dummy variables to represent the categorical variable.
b.
To determine
Obtain the multiple regression equation relating
c.
To determine
Interpret the parameters in the regression equation.
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The St. Lucian Government is interested in predicting the number of weekly riders on the public buses using the following variables:
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Interpret the coefficient of determination.
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Chapter 15 Solutions
Modern Business Statistics with Microsoft Office Excel (with XLSTAT Education Edition Printed Access Card)
Ch. 15.2 - 1. The estimated regression equation for a model...Ch. 15.2 - Consider the following data for a dependent...Ch. 15.2 - Prob. 3ECh. 15.2 - 4. A shoe store developed the following estimated...Ch. 15.2 - The owner of Showtime Movie Theaters, Inc. would...Ch. 15.2 - NFL Winning Percentage. The National Football...Ch. 15.2 - Prob. 7ECh. 15.2 - Scoring Cruise Ships. The Condé Nast Traveler Gold...Ch. 15.2 - The Professional Golfers Association (PGA)...Ch. 15.2 - Baseball Pitcher Performance. Major League...
Ch. 15.3 - 11. In exercise 1, the following estimated...Ch. 15.3 - 12. In exercise 2, 10 observations were provided...Ch. 15.3 - Prob. 13ECh. 15.3 - Prob. 14ECh. 15.3 - 15. In exercise 5, the owner of Showtime Movie...Ch. 15.3 - Prob. 16ECh. 15.3 - In part (d) of exercise 9, data contained in the...Ch. 15.3 - Prob. 18ECh. 15.5 - In exercise 1, the following estimated regression...Ch. 15.5 - Prob. 20ECh. 15.5 - Prob. 21ECh. 15.5 - Prob. 22ECh. 15.5 - Testing Significance in Theater Revenue. Refer to...Ch. 15.5 - Testing Significance in Predicting NFL Wins. The...Ch. 15.5 - The Condé Nast Traveler Gold List provides ratings...Ch. 15.5 - Prob. 26ECh. 15.6 - Prob. 27ECh. 15.7 - 32. Consider a regression study involving a...Ch. 15.7 - Prob. 33ECh. 15.7 - 34. Management proposed the following regression...Ch. 15.7 - Repair Time. Refer to the Johnson Filtration...Ch. 15.7 - Prob. 36ECh. 15.7 - Prob. 37ECh. 15.8 - Prob. 40ECh. 15.8 - Exercise 5 gave the following data on weekly gross...Ch. 15.8 - The following table reports the price, horsepower,...Ch. 15 - 49. The admissions officer for Clearwater College...Ch. 15 - The personnel director for Electronics Associates...Ch. 15 - Prob. 46SECh. 15 - Recall that in exercise 44, the admissions officer...Ch. 15 - Recall that in exercise 45 the personnel director...Ch. 15 - Fortune magazine publishes an annual list of the...Ch. 15 - The Department of Energy and the U.S....Ch. 15 - The Tire Rack, an online distributor of tires and...Ch. 15 - The National Basketball Association (NBA) records...Ch. 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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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_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_forwardBill wants to explore factors affecting work stress. He would like to examine the relationship between age, number of years at the workplace, perceived social support, and work stress. He collects data on the variables from 100 employees (males and females) working in banks. The research question is How accurately can work stress be predicted from linear combination of the predictors (age, social support, number of years at the workplace)? Conduct a multiple regression analysis to answer the following questions: What is the regression equation for all the predictors? Write a results section based on your analysis that answers the research question.arrow_forward
- Bill wants to explore factors affecting work stress. He would like to examine the relationship between age, number of years at the workplace, perceived social support, and work stress. He collects data on the variables from 100 employees (males and females) working in banks. The research question is How accurately can work stress be predicted from linear combination of the predictors (age, social support, number of years at the workplace)? Conduct a multiple regression analysis to answer the following questions: What is the relationship of age, number of years, and social support with work stress? Is the regression significant? If yes, what does it indicate?arrow_forwardIn a useful simple linear regression analysis, the independent variable… is used to predict other independent variables is used to predict the dependent variable has no effect on the dependent variable is the variable that is being predicted using the regression equationarrow_forward3arrow_forward
- Researchers used weight in Kilograms (Y) as a dependent variable and Lean Body Weight (X1) and Mean Daily Caloric Intake (X2) as independent variables. a. Is the coefficient of Mean Daily Caloric Intake statistically distinguishable from 0? b. Perform a hypothesis test. c. Write the regression equation based on the results d. What is the predicted value of the weight of an obese girl if her lean body weight is 50.0 and mean daily caloric intake is 2000? e. What assumptions must be made in this experiment? Are they satisfied? f. Calculate the R2 value? Interpret it. g. Would you recommend the model? Why or why not?arrow_forwarda. find the equation of the regression line? b. the best-predicted crash fatality rate for a year in which there are 500 metric tons of lemon imports is _?_ facilitates per 100,000 population,arrow_forwardYou use “number of hours spent relaxing” as the dependent variable in a study. Choose two possible (and relevant) independent variables and state a clear hypothesis for each relationship.arrow_forward
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