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 15.5, Problem 26E
Testing Significance in Baseball Pitcher Performance. In exercise 10, data showing the values of several pitching statistics for a random sample of 20 pitchers from the American League of Major League Baseball were provided. In part (c) of this exercise an estimated regression equation was developed to predict the average number of runs given up per inning pitched (R/IP) given the average number of strikeouts per inning pitched (SO/IP) and the average number of home runs per inning pitched (HR/IP).
- a. Use the F test to determine the overall significance of the relationship. What is your conclusion at the .05 level of significance?
- b. Use the t test to determine the significance of each independent variable. What is your conclusion at the .05 level of significance?
10. Baseball Pitcher Performance. Major League Baseball (MLB) consists of teams that play in the American League and the National League. MLB collects a wide variety of team and player statistics. Some of the statistics often used to evaluate pitching performance are as follows:
ERA: The average number of earned runs given up by the pitcher per nine innings. An earned run is any run that the opponent scores off a particular pitcher except for runs scored as a result of errors.
SO/IP: The average number of strikeouts per inning pitched.
HR/IP: The average number of home runs per inning pitched.
R/IP: The number of runs given up per inning pitched.
The following data show values for these statistics for a random sample of 20 pitchers from the American League for a full season.
- a. Develop an estimated regression equation that can be used to predict the average number of runs given up per inning given the average number of strikeouts per inning pitched.
- b. Develop an estimated regression equation that can be used to predict the average number of runs given up per inning given the average number of home runs per inning pitched.
- c. Develop an estimated regression equation that can be used to predict the average number of runs given up per inning given the average number of strikeouts per inning pitched and the average number of home runs per inning pitched.
- d. A. J. Burnett, a pitcher for the New York Yankees, had an average number of strikeouts per inning pitched of .91 and an average number of home runs per inning of .16. Use the estimated regression equation developed in part (c) to predict the average number of runs given up per inning for A. J. Burnett. (Note: The actual value for R/IP was .6.)
- e. Suppose a suggestion was made to also use the earned run average as another independent variable in part (c). What do you think of this suggestion?
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Regarding the two variables under consideration in a regression analysis,
a. what is the dependent variable called?
b. what is the independent variable called?
Scores made by students in a statistics class in the midterm and final examination aregiven below:
Student
Mid-term
Final
1
98
90
2
66
74
3
100
98
4
96
88
5
88
80
6
45
62
7
76
78
8
60
74
9
74
86
10
82
80
Develop a regression equation which may be used to predict final examination scoresfrom the mid-term score.
Annual Income. The Census Bureau collects data on income by educational attainment, sex, and age. Results are published in Current Population Reports. From a random sample of 75 males between the ages of 25 and 50, all of whom have at least a ninth-grade education, data were collected on age, number of years of school completed, and annual income. We performed a multiple regression analysis for annual income (in thousands of dollars) with the variables age and number of years of school completed as predictor variables. The resulting output is shown in Output A.21.
a. Use the computer output to obtain the regression equation for annual income in terms of age and number of years of school completed.
b. Apply the regression equation to predict the annual income of a male who is 32 years old and has completed exactly 4 years of college (i.e., 16 years of school).
c. Find and interpret the coefficient of determination, R2
d. Find and interpret the standard error of the estimate.
e. At the…
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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