Introductory Statistics (10th Edition)
10th Edition
ISBN: 9780321989178
Author: Neil A. Weiss
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Textbook Question
Chapter B.6, Problem 116E
Advertising and Sales. Refer to Exercise B.85 on page B-113, where we considered the regression of total sales (sales) on expenditures for three primary means of advertising—television (tv), magazines (mag), and radio (radio)—for a household-appliance manufacturer. Use Output B.70 on pages B-116–B-117 to do the following.
- a. Use the maximum-R2 criterion to obtain a regression equation for these data.
- b. Use the adjusted-R2 criterion to obtain a regression equation for these data.
- c. Use the Mallows’ Cp criterion to obtain a regression equation for these data.
- d. Do the three methods used in parts (a), (b), and (c) yield the same final regression equation? If so, is that always the case?
OUTPUT B.70 Output for Exercises B.85, B.99, and B.116
Predictor variable is tv
Predictor variable is mag
Predictor variable is radio
OUTPUT B.70 (cont.) Output for Exercises B.85, B.99, and B.116
Predictor variables are tv and mag
Predictor variables are tv and radio
Predictor variables are mag and radio
Predictor variables are tv, mag, and radio
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
Corvette, Ferrari, and Jaguar produced a variety of classic cars that continue to increase in value. The data showing the rarity rating (1–20) and the high price ($1000s) for 15 classic cars is contained in the Excel Online file below. Construct a spreadsheet to answer the following questions.
Part I. Run two regressions in Excel using the provided Excel file “Layoffs”.The Excel file Layoffs provides data on 50 manufacturing workers who lost their jobs due to layoffs. The
data includes the following list of variables:Weeks – the number of weeks a manufacturing worker has been without a jobAge – the age of the workerEducation – the number of years of education of the workerMarried – a dummy variable, equal to 1 if the worker is married, 0 otherwiseHead – a dummy variable, equal to 1 if the worker is a head of household, 0 otherwiseTenure – the number of years on the previous jobManager – a dummy variable, equal to 1 if the worker had a management occupation, 0 otherwise Sales – a dummy variable, equal to 1 if the worker had an occupation in sales, 0 otherwise
1. Run a simple regression with a dependent variable Weeks and an independent variable Age. Create the regular and standardized residual plots for the simple regression.
2. Run a multiple regression with a dependent…
Sam Jones has 2 years of historical sales data for his company. He is applyingfor a business loan and must supply his projections of sales by month for thenext 2 years to the bank.
a. Using the data from Table 6–12, provide a regression forecast for timeperiods 25 through 48.b. Does Sam’s sales data show a seasonal pattern?
Chapter B Solutions
Introductory Statistics (10th Edition)
Ch. B.1 - Regarding the regression of a response variable,...Ch. B.1 - Fill in the blanks. a. The assumption that all...Ch. B.1 - Answer true or false to each of the following...Ch. B.1 - Prob. 4ECh. B.1 - In each of Exercises B.5B.14, a. decide whether...Ch. B.1 - Prob. 6ECh. B.1 - Prob. 7ECh. B.1 - In each of Exercises B.5B.14, a. decide whether...Ch. B.1 - In each of Exercises B.5B.14, a. decide whether...Ch. B.1 - In each of Exercises B.5B.14, a. decide whether...
Ch. B.1 - In each of Exercises B.5B.14, a. decide whether...Ch. B.1 - Prob. 12ECh. B.1 - In each of Exercises B.5B.14, a. decide whether...Ch. B.1 - In each of Exercises B.5B.14, a. decide whether...Ch. B.1 - Consider the scatterplot of y versus x in Output...Ch. B.1 - Consider the scatterplot of y versus x in Output...Ch. B.1 - Prob. 17ECh. B.1 - Prob. 18ECh. B.1 - If one or both of the assumptions of...Ch. B.1 - Prob. 20ECh. B.1 - Prob. 21ECh. B.1 - Prob. 22ECh. B.1 - Prob. 23ECh. B.1 - Gasoline Mileage Ratings. Gasoline mileage and...Ch. B.1 - Hip Fracture Rates. In the paper Very Low Rates of...Ch. B.1 - Prob. 26ECh. B.1 - Prob. 27ECh. B.1 - Prob. 28ECh. B.1 - Prob. 29ECh. B.1 - Gasoline Mileage Ratings. Refer to Exercise B.24,...Ch. B.1 - Hip Fracture Rates. Refer to Exercise B.25, where...Ch. B.1 - Drosophila Life-span. In the paper Extended...Ch. B.1 - Protein Content of Wheat. In their text, Methods...Ch. B.1 - Pine Tree Volume. Table B.2 on page B-5 provides...Ch. B.2 - Give an example of a. a second-degree polynomial...Ch. B.2 - In the polynomial regression equation y = 8 + 3x ...Ch. B.2 - Answer true or false to each of the following...Ch. B.2 - Explain why it is difficult to interpret the...Ch. B.2 - Fill in the blanks. a. A predictor variable is...Ch. B.2 - Answer true or false to each of the following...Ch. B.2 - Refer to the scatterplots in Outputs B.32(a) and...Ch. B.2 - Fill in the blanks. a. In the _______ method for...Ch. B.2 - Answer true or false to each of the following...Ch. B.2 - Stopping Distance. In their text Methods of...Ch. B.2 - Hour of Birth. In the paper increased Frequency of...Ch. B.2 - Silica Gel. Silica gel is a substance that absorbs...Ch. B.2 - Note: The data for the Using Technology exercises...Ch. B.2 - Hour of Birth. Refer to Exercise B.45, where the...Ch. B.2 - Silica Gel. Refer to Exercise B.46, where the...Ch. B.2 - Gasoline Mileage Ratings. Refer to Exercise B.24...Ch. B.2 - Protein Content of Wheat. Refer to Exercise B.33...Ch. B.2 - Satellite Orbits. Each issue of the magazine Ad...Ch. B.2 - Pine Tree Volume. In Example B.6 on page B-4, we...Ch. B.3 - Explain the difference between a quantitative...Ch. B.3 - In predicting a person's income, identify two...Ch. B.3 - In predicting the change in blood pressure for...Ch. B.3 - Fill in the blanks. a. A ___ predictor variable is...Ch. B.3 - Prob. 59ECh. B.3 - Answer true or false to each of the following...Ch. B.3 - For the regression equation y = 15 + 2x1 + 4x2 ...Ch. B.3 - Refer to Exercise B.61: a. Do the slopes of the...Ch. B.3 - Consider the regression equation y = 0 + 1 x1+ 2x2...Ch. B.3 - Prob. 64ECh. B.3 - Prob. 65ECh. B.3 - Prob. 66ECh. B.3 - Home Sale Prices. Refer to Example B.18 on page...Ch. B.3 - Mental Tasks and Drugs. In the text Statistical...Ch. B.3 - Gasoline Mileage Ratings. Refer to Exercise B.66...Ch. B.3 - Home Sale Prices. Refer to Exercise B.67 regarding...Ch. B.3 - Mental Tasks and Drugs. Refer to Exercise B.68...Ch. B.3 - Hip Fracture Rates. Refer to Exercise B.25 on page...Ch. B.3 - Television Viewing. The results of a study on...Ch. B.3 - Glue Strength. In the text Quality Control and...Ch. B.4 - Explain why the interpretation of the regression...Ch. B.4 - Answer true or false to each of the following...Ch. B.4 - Explain what is meant by multicollinearity.Ch. B.4 - Fill in the blanks. a. Consider a regression model...Ch. B.4 - Prob. 79ECh. B.4 - Prob. 80ECh. B.4 - Fill in the blanks. a. If predictor variable x1...Ch. B.4 - Answer true or false to each of the following...Ch. B.4 - State four ways to detect the presence of...Ch. B.4 - Prob. 84ECh. B.4 - Prob. 85ECh. B.4 - Prob. 86ECh. B.4 - Prob. 87ECh. B.4 - Prob. 88ECh. B.4 - Graduation Rates. Refer to Exercise B.86, where we...Ch. B.4 - Prob. 90ECh. B.4 - Gasoline Mileage Ratings. Refer to Exercise B.84,...Ch. B.4 - Graduation Rules. Refer to Exercise B.86, where we...Ch. B.5 - Explain what is meant by the variable selection...Ch. B.5 - Prob. 94ECh. B.5 - Fill in the blanks. a. In the forward selection...Ch. B.5 - Prob. 96ECh. B.5 - Answer true or false to each of the following...Ch. B.5 - Prob. 98ECh. B.5 - Prob. 99ECh. B.5 - Prob. 100ECh. B.5 - Prob. 101ECh. B.5 - Suppose that x1, x2, x3, and x4 are predictor...Ch. B.5 - Prob. 103ECh. B.5 - Graduation Rates. Refer to Exercise B.92 on page...Ch. B.5 - Home Sale Prices. In Example B. 18 on page B-67,...Ch. B.5 - Home Sale Prices. In Example B.18 on page B-67, we...Ch. B.5 - Infant Mortality Rates. In the article Children's...Ch. B.6 - Consider a multiple linear regression relating the...Ch. B.6 - Prob. 109ECh. B.6 - Prob. 110ECh. B.6 - Answer true or false to each of the following...Ch. B.6 - Explain the similarities and differences between...Ch. B.6 - Fill in the blanks. a. In the Mallows Cp...Ch. B.6 - Answer true or false to each of the following...Ch. B.6 - Gasoline Mileage Ratings. Refer to Exercise B.84...Ch. B.6 - Advertising and Sales. Refer to Exercise B.85 on...Ch. B.6 - Graduation Rates. Refer to Exercise B.86 on page...Ch. B.6 - Suppose that x1, x2, x3, and x4 are predictor...Ch. B.6 - Suppose that x1 x2, x3, and x4 are predictor...Ch. B.6 - Gasoline Mileage Ratings. Refer to Exercise B.91...Ch. B.6 - Graduation Rates. Refer to Exercise B.92 on page...Ch. B.6 - Home Sale Prices. Refer to Exercise B.105 on page...Ch. B.6 - Body Fat. Refer to Exercise B.106 on page B-143,...Ch. B.6 - Infant Mortality Rates. Refer to Exercise B.107 on...Ch. B.7 - List six problems that can arise in the collection...Ch. B.7 - Prob. 126ECh. B.7 - Prob. 127ECh. B.7 - Give an example of how a nonrepresentative sample...Ch. B.7 - Discuss the effect on a regression analysis of not...Ch. B.7 - Explain how multicollinearity can adversely affect...Ch. B.7 - Briefly describe what is meant by the problem of...Ch. B.7 - Answer true or false to each of the following...Ch. B.7 - Prob. 133ECh. B.7 - Discuss the advantages of using data collected...Ch. B.7 - Describe the potential effects of outliers on...Ch. B.7 - Prob. 136ECh. B.7 - Regarding regression analysis: a. What assumptions...Ch. B.7 - Answer true or false to each of the following...Ch. B.7 - Answer true or false to each of the following...Ch. B.7 - Discuss what G. E. P. Box might have meant when he...Ch. B.7 - Regarding model validation in regression: a. What...Ch. B - Explain what is meant when we say that a nonlinear...Ch. B - Answer true or false to the following statements...Ch. B - Prob. 3RPCh. B - Prob. 4RPCh. B - Answer true or false to each of the following...Ch. B - Paper Strength. In their text, Introduction to...Ch. B - Answer true or false to each of the following...Ch. B - Prob. 8RPCh. B - Explain what is meant when we say that a...Ch. B - OUTPUT B.95 Output for Problem 10 Regression...Ch. B - In regressing a response variable on several...Ch. B - Answer true or false to each of the following...Ch. B - Fill in the blanks. a. Multicollinearity is...Ch. B - Prob. 14RPCh. B - Explain why selecting a regression equation using...Ch. B - Answer true or false to each of the following...Ch. B - Fill in the blanks. a. In the _____ method, we...Ch. B - Patent Production. In the report The State New...Ch. B - Prob. 19RPCh. B - Prob. 20RPCh. B - Patent Production. Refer to Problem 18. where we...Ch. B - Prob. 22RPCh. B - Prob. 23RPCh. B - What are the possible consequences of the presence...Ch. B - Windmill Output. Refer to Problem 3, where we...Ch. B - Paper Strength. Refer to Problem 6, where we...Ch. B - Diabetes. Refer to Problem 10, where we considered...Ch. B - Hospital Stalling. Refer to Problem 14, where we...Ch. B - Patent Production. Refer to Problem 18, where we...Ch. B - Patent Production. Refer to Problem 29, where we...Ch. B - Recall from Chapter 1 of your text that the Focus...Ch. B - At the beginning of this module on page B-l, we...
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- 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_forwardThe U.S. Postal Service is attempting to reduce the number of complaints made by the public against its workers. To facilitate this task, a staff analyst for the service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year. The analyst ran a simple linear regression in SPSS. The results are shown below. The current minimum wage is $5.15. If an employee earns the minimum wage, how many complaints can that employee expect to receive? Is the regression coefficient statistically significant? How can you tell?arrow_forwardSTER. 1. Wine Consumption. The table below gives the U.S. adult wine consumption, in gallons per person per year, for selected years from 1980 to 2005. a) Create a scatterplot for the data. Graph the scatterplot Year Wine below. Consumption 2.6 b) Determine what type of model is appropriate for the 1980 data. 1985 2.3 c) Use the appropriate regression on your calculator to find a Graph the regression equation in the same coordinate plane below. d) According to your model, in what year was wine consumption at a minimum? A e) Use your model to predict the wine consumption in 2008. 1990 2.0 1995 2.1 2000 2.5 2005 2.8arrow_forward
- According to human capital theory, a person’s earning is linked to her level of education – there is a relationship between workers income and years of education. Using data from the Labour Force Survey, a researcher found the following regression results for earnings on intercept, years of education, experience, and experience squared: Earnings = 5.24 + 0.035 educ + 0.165 exper – 0.003 exper2 (2.45) (0.012) (0.031) (0.001) Construct a 95% confidence interval for the effect of years of education on earnings ? 2. Consider an individual with 8 years of experience. What would you expect to be the return to two (2) additional years of experience (the effect on earnings)? 3. According to economic theory,…arrow_forward-Using the data in Table 6–11, answer the following: What is the slope? What is the intercept? Write the regression equation. Calculate a regression forecast for month 25.arrow_forwardArmer Company is accumulating data to use in preparing its annual profit plan for the coming year. The cost behavior pattern of the maintenance costs must be determined. The accounting staff has suggested the use of linear regression to derive an equation for maintenance hours and costs. Data regarding the maintenance hours and costs for the last year and the results of the regression analysis follow: Month Maintenance Cost Machine Hours Jan. $ 4,200 480 Feb. 3,000 320 Mar. 3,600 400 Apr. 2,820 300 May 4,350 500 June 2,960 310 July 3,030 320 Aug. 4,470 520 Sept. 4,260 490 Oct. 4,050 470 Nov. 3,300 350 Dec. 3,160 340 Sum $ 43,200 4,800 Average $ 3,600 $ 400 Average cost per hour $ 9.00 a (intercept) $ 684.65 b (coefficient) 7.2884 Standard error of the estimate 34.469 R-squared 0.99724 t-value for b 60.105…arrow_forward
- Armer Company is accumulating data to use in preparing its annual profit plan for the coming year. The cost behavior pattern of the maintenance costs must be determined. The accounting staff has suggested the use of linear regression to derive an equation for maintenance hours and costs. Data regarding the maintenance hours and costs for the last year and the results of the regression analysis follow: Month Maintenance Cost Machine Hours Jan. $ 4,200 480 Feb. 3,000 320 Mar. 3,600 400 Apr. 2,820 300 May 4,350 500 June 2,960 310 July 3,030 320 Aug. 4,470 520 Sept. 4,260 490 Oct. 4,050 470 Nov. 3,300 350 Dec. 3,160 340 Sum $ 43,200 4,800 Average $ 3,600 $ 400 Average cost per hour $ 9.00 a (intercept) $ 684.65 b (coefficient) 7.2884 Standard error of the estimate 34.469 R-squared 0.99724 t-value for b 60.105…arrow_forwardThe managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through o. Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs OxBillable Hours (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) Monthly Overhead Costs and Billable Hours Data Overhead Costs $385,000 Billable Hours 3,000 $425,000 4,000 $445.000 5,000 $497,000 6,000 $570,000 7,000 $590,000 8,000arrow_forwardArmer Company is accumulating data to use in preparing its annual profit plan for the coming year. The cost behavior pattern of the maintenance costs must be determined. The accounting staff has suggested the use of linear regression to derive an equation for maintenance hours and costs. Data regarding the maintenance hours and costs for the last year and the results of the regression analysis follow: Month Maintenance Cost Machine Hours Jan. $ 5,050 820 Feb. 3,850 660 Mar. 4,450 740 Apr. 3,670 640 May 5,200 840 June 3,810 650 July 3,880 660 Aug. 5,320 940 Sept. 5,110 830 Oct. 4,900 810 Nov. 4,150 690 Dec. 4,010 680 Sum $ 53,400 8,960 Average $ 4,450 $ 747 Average cost per hour $ 6.00 a (intercept) $ 194.33 b (coefficient) 6.2201 Standard error of the estimate 144.247 R-squared 0.9517 t-value for b 14.030…arrow_forward
- For the provided data, develop a regression model for overall satisfaction as a function of years of service and department that has the largest R. Note that the categorical variable department has multiple levels and will require the use of multiple dummy variables. Which department, if any, has the highest impact on roduction satisfaction? Production Production E Click the icon to view the job satisfaction data. Determine the regression model for overall satisfaction as a function of years of service and department that has the largest R. Let "Administrative" be the baseline department, let X, represent Maintenance, let X, represent Management, let X, represent Production, let X, represent Quality Control, and let Xg represent Shipping / Receiving, coding each department variable with a 1 if the person is in that department and 0 otherwise. In addition, let Xe represent Years. Enter the terms of the equation so that the X-values are in ascending numerical order by base. Select the…arrow_forwardThe training manager of a company that assembles and exports pool pumps wants to know if there is a link between the number of hours spent by assembly workers in training and their productivity on the job. A random sample of 10 assembly workers was selected and their performances evaluated. Use the information below to calculate the slope of the regression equation (rounded off to four decimals). Training hours (x) 20 36 20 38 40 33 32 28 40 24 Output (y) 40 70 44 56 60 48 62 54 63 38 Use the following measures for further calculations: Ex 311 Zy = 535 Exy 17240 Ex² = 10213 Ey² = 29649 %D %3D %3D A. 1.1120 B. 0.5860 • C. 0.5269 D. 18.9168arrow_forwardPlease help with unanswered questions. Thank you!arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- College AlgebraAlgebraISBN:9781305115545Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage LearningAlgebra and Trigonometry (MindTap Course List)AlgebraISBN:9781305071742Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage Learning
- Functions and Change: A Modeling Approach to Coll...AlgebraISBN:9781337111348Author:Bruce Crauder, Benny Evans, Alan NoellPublisher:Cengage LearningAlgebra & Trigonometry with Analytic GeometryAlgebraISBN:9781133382119Author:SwokowskiPublisher:Cengage
College Algebra
Algebra
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:Cengage Learning
Algebra and Trigonometry (MindTap Course List)
Algebra
ISBN:9781305071742
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:Cengage Learning
Functions and Change: A Modeling Approach to Coll...
Algebra
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Cengage Learning
Algebra & Trigonometry with Analytic Geometry
Algebra
ISBN:9781133382119
Author:Swokowski
Publisher:Cengage
Time Series Analysis Theory & Uni-variate Forecasting Techniques; Author: Analytics University;https://www.youtube.com/watch?v=_X5q9FYLGxM;License: Standard YouTube License, CC-BY
Operations management 101: Time-series, forecasting introduction; Author: Brandoz Foltz;https://www.youtube.com/watch?v=EaqZP36ool8;License: Standard YouTube License, CC-BY