Modern Business Statistics with Microsoft Office Excel (with XLSTAT Education Edition Printed Access Card) (MindTap Course List)
6th Edition
ISBN: 9781337115186
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: Cengage Learning
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Chapter 15.5, Problem 26E
a.
To determine
Perform F test to determine the overall significance of the relationship.
Draw conclusion at
b.
To determine
Perform t test to determine the significance of each independent variable and draw conclusion at the 0.05 level of significance.
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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
Modern Business Statistics with Microsoft Office Excel (with XLSTAT Education Edition Printed Access Card) (MindTap Course List)
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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- Life 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_forwardNFL Winning Percentage. The National Football League (NFL) records avariety of performance data for individuals and teams. To investigate theimportance of passing on the percentage of games won by a team, the following data show the conference (Conf), average number of passingyards per attempt (Yds/Att), the number of interceptions thrown perattempt (Int/Att), and the percentage of games won (Win%) for a randomsample of 16 NFL teams for one full season. a. Develop the estimated regression equation that could be used topredict the percentage of games won given the average number ofpassing yards per attempt.b. Develop the estimated regression equation that could be used to predict the percentage of games won given the number ofinterceptions thrown per attempt.c. Develop the estimated regression equation that could be used topredict the percentage of games won given the average number ofpassing yards per attempt and the number of interceptions thrown per attempt.d. The average number of…arrow_forwardAppendix B Data Sets. In Exercises 13–16, refer to the indicated data set in Appendix B and use technology to obtain results. Predicting IQ Score Refer to Data Set 8 “IQ and Brain Size” in Appendix B and find the best regression equation with IQ score as the response (y) variable. Use predictor variables of brain volume and/or body weight. Why is this equation best? Based on these results, can we predict someone’s IQ score if we know their brain volume and body weight? Based on these results, does it appear that people with larger brains have higher IQ scores?arrow_forward
- Improving SAT scores. Chance (Winter 2001) published a study of students who paid a private coach to help them improve their Scholastic Assessment Test (SAT) scores. Multiple regression was used to estimate the effect of coaching on SAT–Mathematics scores. Data on 3,492 students (573 of whom were coached) were used to fit the model E(y) = β0 + β1x1 + β2x2,where y = SAT–Math score,x1 = score on PSAT, and x2 ={1 if student was coached, 0 if not}. (A). The fitted model had an adjusted R2 value of .76. Interpret this result. (B). The estimate of β2 in the model was 19, with a standard error of 3. Use this information to form a 95% confidence interval for β2. Interpret the interval. (C). Based on the interval, part b, what can you say about the effect of coaching on SAT–Math scores? (D). As an alternative model, the researcher added several ‘‘control’’ variables, including dummy variables for student ethnicity (x3,x4, and x5), a socioeconomic status index variable (x6), two variables that…arrow_forwardCity Fuel Consumption: Finding the Best Multiple Regression Equation. In Exercises 9–12, refer to the accompanying table, which was obtained using the data from 21 cars listed in Data Set 20 “Car Measurements” in Appendix B. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi /gal). If exactly two predictor (x) variables are to be used to predict the city fuel consumption, which two variables should be chosen? Why?arrow_forwardTraining Dept. of Nimrod Inc wants to develop a regression-based compensation model (compensation in $ per year, Comp) for its mid-level managers to encourage performance, loyalty, and continuing education based on three variables. ▪ Business unit-profitability (Profit per year in $). ▪ Working experiences in Nimrod Inc (Years). ▪ Whether or not a manager has a graduate degree (Grads). If a manager has a graduate degree equals 1, 0 otherwise. Table Attached Question: At the 5% significance level, is the overall regression model significantarrow_forward
- a. Compute the Pearson correlation statistic b. Find the linear regression equation for predicting Y from X. c. Explain the difference between b in a linear regression equation and the Pearson correlation statistic.arrow_forwardCity Fuel Consumption: Finding the Best Multiple Regression Equation. In Exercises 9–12, refer to the accompanying table, which was obtained using the data from 21 cars listed in Data Set 20 “Car Measurements” in Appendix B. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi /gal). A Honda Civic weighs 2740 lb, it has an engine displacement of 1.8 L, and its highway fuel consumption is 36 mi/gal. What is the best predicted value of the city fuel consumption? Is that predicted value likely to be a good estimate? Is that predicted value likely to be very accurate?arrow_forward
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