Statistics for Business & Economics, Revised (with XLSTAT Education Edition Printed Access Card)
13th Edition
ISBN: 9781337094160
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: Cengage Learning
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Textbook Question
Chapter 14.8, Problem 45E
Given are data for two variables, x and y.
| xi | 6 | 11 | 15 | 18 | 20 |
| yi | 6 | 8 | 12 | 20 | 30 |
- a. Develop an estimated regression equation for these data.
- b. Compute the residuals.
- c. Develop a plot of the residuals against the independent variable x. Do the assumptions about the error terms seem to be satisfied?
- d. Compute the standardized residuals.
- e. Develop a plot of the standardized residuals against y. What conclusions can you draw from this plot?
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Chapter 14 Solutions
Statistics for Business & Economics, Revised (with XLSTAT Education Edition Printed Access Card)
Ch. 14.2 - Given are five observations for two variables, x...Ch. 14.2 - Given are five observations for two variables, x...Ch. 14.2 - Given are five observations collected in a...Ch. 14.2 - The following data give the percentage of women...Ch. 14.2 - Brawdy Plastics, Inc., produces plastic seat belt...Ch. 14.2 - The National Football League (NFL) records a...Ch. 14.2 - A sales manager collected the following data on...Ch. 14.2 - The American Association of Individual Investors...Ch. 14.2 - Prob. 9ECh. 14.2 - On March 31, 2009, Ford Motor Companys shares were...
Ch. 14.2 - To help consumers in purchasing a laptop computer,...Ch. 14.2 - Concur Technologies, Inc., is a large...Ch. 14.2 - To the Internal Revenue Service, the...Ch. 14.2 - A large city hospital conducted a study to...Ch. 14.3 - The data from exercise 1 follow. xi 1 2 3 4 5 yi 3...Ch. 14.3 - The data from exercise 2 follow. xi 3 12 6 20 14...Ch. 14.3 - The data from exercise 3 follow. xi 2 6 9 13 20 yi...Ch. 14.3 - The following data show the brand, price (), and...Ch. 14.3 - In exercise 7 a sales manager collected the...Ch. 14.3 - Bicycling, the worlds leading cycling magazine,...Ch. 14.3 - An important application of regression analysis in...Ch. 14.3 - Refer to exercise 9, where the following data were...Ch. 14.5 - The data from exercise 1 follow. xi 1 2 3 4 5 yi 3...Ch. 14.5 - The data from exercise 2 follow. xi 3 12 6 20 14...Ch. 14.5 - The data from exercise 3 follow. xi 2 6 9 13 20 yi...Ch. 14.5 - In exercise 18 the data on price () and the...Ch. 14.5 - To identify high-paying jobs for people who do not...Ch. 14.5 - In exercise 8 ratings data on x = the quality of...Ch. 14.5 - Refer to exercise 21, where data on production...Ch. 14.5 - Refer to exercise 9, where the following data were...Ch. 14.5 - In exercise 20, data on x = weight (pounds) and y...Ch. 14.6 - The data from exercise 1 follow. xi 1 2 3 4 5 yi 3...Ch. 14.6 - The data from exercise 2 follow. xi 3 12 6 20 14...Ch. 14.6 - The data from exercise 3 follow. xi 2 6 9 13 20 yi...Ch. 14.6 - The following data are the monthly salaries y and...Ch. 14.6 - In exercise 7, the data on y = annual sales (...Ch. 14.6 - In exercise 13, data were given on the adjusted...Ch. 14.6 - Refer to exercise 21, where data on the production...Ch. 14.6 - In exercise 12, the following data on x = average...Ch. 14.7 - The commercial division of a real estate firm is...Ch. 14.7 - Following is a portion of the computer output for...Ch. 14.7 - A regression model relating x, number of...Ch. 14.7 - A 2012 suvey conducted by Idea Works provided data...Ch. 14.7 - Automobile racing, high-performance driving...Ch. 14.8 - Given are data for two variables, x and y. xi 6 11...Ch. 14.8 - The following data were used in a regression...Ch. 14.8 - Data on advertising expenditures and revenue (in...Ch. 14.8 - Refer to exercise 7, where an estimated regression...Ch. 14.8 - In 2011 home prices and mortgage rates dropped so...Ch. 14.9 - Consider the following data for two variables, x...Ch. 14.9 - Consider the following data for two variables, x...Ch. 14.9 - Charity Navigator is Americas leading independent...Ch. 14.9 - Many countries, especially those in Europe, have...Ch. 14.9 - Prob. 54ECh. 14 - Does a high value of r2 imply that two variables...Ch. 14 - In your own words, explain the difference between...Ch. 14 - What is the purpose of testing whether 1 = 0? If...Ch. 14 - The Dow Jones Industrial Average (DJIA) and the...Ch. 14 - Is the number of square feet of living space a...Ch. 14 - One of the biggest changes in higher education in...Ch. 14 - Jensen Tire Auto is in the process of deciding...Ch. 14 - In a manufacturing process the assembly line speed...Ch. 14 - A sociologist was hired by a large city hospital...Ch. 14 - The regional transit authority for a major...Ch. 14 - A marketing professor at Givens College is...Ch. 14 - The Transactional Records Access Clearinghouse at...Ch. 14 - The Toyota Camry is one of the best-selling cars...Ch. 14 - You have been assigned to analyze the risk...Ch. 14 - As part of a study on transportation safety, the...Ch. 14 - Consumer Reports tested 166 different...Ch. 14 - Finding the Best Car Value When trying to decide...Ch. 14 - Buckeye Creek Amusement Park is open from the...
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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_forwardXYZ Corporation Stock Prices The following table shows the average stock price, in dollars, of XYZ Corporation in the given month. Month Stock price January 2011 43.71 February 2011 44.22 March 2011 44.44 April 2011 45.17 May 2011 45.97 a. Find the equation of the regression line. Round the regression coefficients to three decimal places. 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 the stock price to be in January 2012? January 2013?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_forward
- Demand for Candy Bars In this problem you will determine a linear demand equation that describes the demand for candy bars in your class. Survey your classmates to determine what price they would be willing to pay for a candy bar. Your survey form might look like the sample to the left. a Make a table of the number of respondents who answered yes at each price level. b Make a scatter plot of your data. c Find and graph the regression line y=mp+b, which gives the number of respondents y who would buy a candy bar if the price were p cents. This is the demand equation. Why is the slope m negative? d What is the p-intercept of the demand equation? What does this intercept tell you about pricing candy bars? Would you buy a candy bar from the vending machine in the hallway if the price is as indicated. Price Yes or No 50 75 1.00 1.25 1.50 1.75 2.00arrow_forwardDoes Table 1 represent a linear function? If so, finda linear equation that models the data.arrow_forward
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