INTRO.STATISTICS,TECH.UPDT.-W/MYSTATLAB
10th Edition
ISBN: 9780135230008
Author: WEISS
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Concept explainers
Videos
Textbook Question
Chapter A.3, Problem 67E
Custom Home Resales. Refer to Exercise A.46 on page A-16 regarding predicting the selling price of a home in the Equestrian Estates using the predictor variables square footage, number of bedrooms, number of bathrooms, and number of days on the market. Use Output A.11 on pages A-20–A-21 to help answer the following questions.
- a. Explain what it would mean for the assumptions for multiple linear regression inferences to be satisfied with square footage, number of bedrooms, number of bathrooms, and number of days on the market as predictor variables for selling price.
- b. Use the computer output to obtain the coefficient of determination, R2. Interpret your result.
- c. Determine and interpret the standard error of the estimate, se.
- d. Do the data provide sufficient evidence to conclude that, taken together, square footage, number of bedrooms, number of bathrooms, and number of days on the market are useful for predicting selling price? Perform the required hypothesis test at the 1% significance level.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar 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…
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.
The owners of a chain of ice cream stores have the business objective of improving the forecast of daily sales so that staffing shortages can be minimized during the summer season. As a starting point, the owners decide to develop a simple
linear regression model to predict daily sales based on atmospheric temperature. They select a sample of 15 consecutive days. The results are shown in the accompanying table. Complete parts (a) through (f) below.
Click the icon to view the data table.
E Click the icon to view a table of critical values of the Durbin-Watson statistic.
a. Assuming a linear relationship, use the least-squares method to compute the regression coefficients b, and b,.
b, = - 2.7630 (Round to four decimal places as needed.)
%3D
Ice cream sales
b, = (Round to four decimal places as needed.)
%3D
Day Sales ($1,000)
Temperature (°F)
63
1
2
1.52
1.68
71
75
3
1.92
1.79
74
76
4
2.02
2.36
6.
81
2.16
2.69
81
8
84
2.91
88
10
3.17
90
11
12
3.02
3.27
90
93
99
13
3.42
2.84
88
83
14
15…
Chapter A Solutions
INTRO.STATISTICS,TECH.UPDT.-W/MYSTATLAB
Ch. A.1 - A. 1 Regarding linear equations in two or more...Ch. A.1 - Fill in the blanks. a. The graph of a linear...Ch. A.1 - Consider a linear equation y = b0 + b1x1 + b2x2. ...Ch. A.1 - Prob. 4ECh. A.1 - Prob. 5ECh. A.1 - Prob. 6ECh. A.1 - Banquet Room Rental. The banquet room at the...Ch. A.1 - Prob. 8ECh. A.1 - In each of Exercises A.9A.12, a. determine the...Ch. A.1 - In each of Exercises A.9A.12, a. determine the...
Ch. A.1 - In each of Exercises A.9A.12, a. determine the...Ch. A.1 - In each of Exercises A.9A.12, a. determine the...Ch. A.1 - Prob. 13ECh. A.1 - Prob. 14ECh. A.1 - Prob. 15ECh. A.1 - In each of Exercises A.13A.22, you are given the...Ch. A.1 - Prob. 17ECh. A.1 - Prob. 18ECh. A.1 - In each of Exercises A.13A.22, you are given the...Ch. A.1 - Prob. 20ECh. A.1 - Prob. 21ECh. A.1 - In each of Exercises A.13A.22, you are given the...Ch. A.1 - In each of Exercises A.23A.30, we have identified...Ch. A.1 - Prob. 24ECh. A.1 - Prob. 25ECh. A.1 - Prob. 26ECh. A.1 - In each of Exercises A.23A.30, we have identified...Ch. A.1 - Prob. 28ECh. A.1 - Prob. 29ECh. A.1 - Prob. 30ECh. A.1 - Why is it often preferable to use more than one...Ch. A.1 - Grade Prediction. The Statistics Department at a...Ch. A.1 - Prob. 33ECh. A.1 - Blood Pressure Medication. A medical researcher...Ch. A.1 - Infant Mortality Rate. A social scientist wants to...Ch. A.2 - Regarding a scatterplot matrix: a. Identify two of...Ch. A.2 - Regarding the criterion used to decide tits a set...Ch. A.2 - Prob. 38ECh. A.2 - Regarding the variables in a multiple linear...Ch. A.2 - Answer true or false to the following statements...Ch. A.2 - In each of Exercises A.41 and A.42, a. construct...Ch. A.2 - In each of Exercises A.41 and A.42, a. construct...Ch. A.2 - Advertising and Sales. A household-appliance...Ch. A.2 - Corvette Prices. The data on age and price for 10...Ch. A.2 - Graduation Kales. Graduation rates and what...Ch. A.2 - Custom Home Resales. Hanna Properties specializes...Ch. A.2 - Advertising and Sales. Refer to Exercise A.43. Use...Ch. A.2 - Prob. 48ECh. A.2 - Graduation Rates. Refer to Exercise A.45. Use the...Ch. A.2 - Custom Home Resales. Refer to Exercise A.46. Use...Ch. A.3 - Fill in the blanks. a. A measure of total...Ch. A.3 - In this section we introduced a descriptive...Ch. A.3 - Suppose x1, x2, and x3 are predictor variables and...Ch. A.3 - State the four conditions required for making...Ch. A.3 - In each of Exercises A.55A.59, assume the...Ch. A.3 - In each of Exercises A.55A.59, assume the...Ch. A.3 - In each of Exercises A.55A.59, assume the...Ch. A.3 - Prob. 58ECh. A.3 - In each of Exercises A.55A.59, assume the...Ch. A.3 - Fill in the blanks. a. When a sum of squares is...Ch. A.3 - Answer true or false to the following statements...Ch. A.3 - For a particular multiple linear regression...Ch. A.3 - For a particular multiple linear regression...Ch. A.3 - Advertising and Sales. Refer to Exercise A.43 on...Ch. A.3 - Corvette Prices. Refer to Exercise A.44 on page...Ch. A.3 - Graduation Rates. Refer to Exercise A.45 on page...Ch. A.3 - Custom Home Resales. Refer to Exercise A.46 on...Ch. A.3 - Advertising and Sales. Refer to Exercise A.43 on...Ch. A.3 - Corvette Prices. Refer to Exercise A.44 on page...Ch. A.3 - Graduation Rates. Refer to Exercise A.45 on page...Ch. A.3 - Custom Home Resales. Refer to Exercise A.46 on...Ch. A.3 - Suppose that R2 = 1 for a data set. What can you...Ch. A.3 - Suppose that R2 = 0 for a data set. What can you...Ch. A.3 - Use the regression identity for multiple linear...Ch. A.4 - Explain why the predictor variables are useless as...Ch. A.4 - Prob. 76ECh. A.4 - What test statistic is used for a hypothesis test...Ch. A.4 - Answer line or false to the following statements...Ch. A.4 - Advertising and Sales. Refer to Exercise A.43 oil...Ch. A.4 - Prob. 80ECh. A.4 - Graduation Rates. Refer to Exercise A.45 on page...Ch. A.4 - Custom-Home Resales. Refer to Exercise A.46 on...Ch. A.4 - Advertising and Sales. Referring to Exercise A.79,...Ch. A.4 - Prob. 84ECh. A.4 - Graduation Rates. Referring to Exercise A.81, use...Ch. A.4 - Prob. 86ECh. A.5 - What two regression inferences did we discuss in...Ch. A.5 - Prob. 88ECh. A.5 - A sample multiple linear regression equation...Ch. A.5 - Answer true or false to the following statements...Ch. A.5 - Advertising and Sales. Refer to Exercise A.43 on...Ch. A.5 - Corvette Prices. Refer to Exercise A.44 on page...Ch. A.5 - Graduation Rates. Refer to Exercise A.45 on page...Ch. A.5 - Custom-Home Resales. Refer to Exercise A.46 on...Ch. A.5 - Advertising and Sales. Referring to Exercise A.91,...Ch. A.5 - Corvette Sales. Referring to Exercise A.92, use...Ch. A.5 - Graduation Rates. Referring to Exercise A.93, use...Ch. A.5 - Custom-Home Resales. Referring to Exercise A.94,...Ch. A.6 - Fill in the blanks. a. In multiple linear...Ch. A.6 - Describe the difference between a residual and a...Ch. A.6 - Fill in the blanks. a. In multiple linear...Ch. A.6 - Answer true or false to the following statements...Ch. A.6 - Prob. 103ECh. A.6 - Corvette Prices. Refer to Exercise A.44 on page...Ch. A.6 - Advertising and Sales. Refer to Exercise A.43 on...Ch. A.6 - Corvette Prices. Refer to Exercise A.44 on page...Ch. A.6 - Graduation Rates. Refer to Exercise A.45 on page...Ch. A.6 - Custom-Homes Resales. Refer to Exercise A.46 on...Ch. A - For a linear equation y = b0 + b1x1 + b2x2 + b3x3,...Ch. A - Consider the linear equation y = 5 + 4x1 3x2. a....Ch. A - Answer true or false to each of the following...Ch. A - What kind of plot is useful for deciding whether...Ch. A - Prob. 5RPCh. A - Prob. 6RPCh. A - Regarding multiple linear regression analysis: a....Ch. A - Prob. 8RPCh. A - For each of the following sums of squares in...Ch. A - Prob. 10RPCh. A - Prob. 11RPCh. A - Suppose x1 and x2 are predictor variables for a...Ch. A - Fill in the blanks. a. The F-statistic for a test...Ch. A - Answer true or false to each of the following...Ch. A - Which interval is wider: (a) the 95% confidence...Ch. A - What plots did we use in this module to decide...Ch. A - Regarding analysis of residuals, decide in each...Ch. A - Annual Income. The Census Bureau collects data on...Ch. A - Annual Income. Refer to Problem 18 and the...Ch. A - Annual Income. Refer to Problem 18, Outputs...Ch. A - Recall from Chapter 1 (page 34 of your text) that...Ch. A - At the beginning of this module on page A-0, 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 hiring managers want to compare three different employment sources: Newspaper/Magazine, CareerBuilder, and Monster.com. Perform simple regressions as you did above predicting allocations for month 13 for those three employment sources. Which of the following statements would be the best conclusion from your analysis? The model R-square for Monster.com is the highest R-square value of the three platforms. Therefore, management will likely provide the most funding for that platform, and we should focus on that above the other two. The models for Monster.com and Newspaper/Magazine are both significant, which means we should focus on these two platforms over CareerBuilder because management will likely provide us the most funding for those two platforms. The predicted monthly amount for CareerBuilder is lower than the predicted amount for Newspaper/Magazine. Therefore, they should expect the lowest amount of funding for CareerBuilder out of all of the three, and should concentrate on…arrow_forwardSuppose that a kitchen cabinet warehouse company would like to be able to predict the area of a customer’s kitchen using the number of cabinets and the kitchen ceiling height. To do so data is collected on the following variables from a random sample of customers: Area – area of the kitchen in square feet Height – ceiling height in the kitchen (from floor to ceiling) in inches Cabinets – number of cabinets in the kitchen Suppose that a multiple linear regression model was fit to the data and that the following output resulted: Coefficients: (Intercept)HeightCabinets Estimate-57.98771.2760.3393 Std. Error8.63820.26430.1302 t value -6.7134.8282.607 Pr(>|t|)2.75e-074.44e-050.0145 Why is the interpretation of the constant term (i.e. "intercept") not meaningful for this example? The predicted area will be negative when the number of cabinets is zero and the height of the kitchen is also zero. But we cannot have a negative area, nor a kitchen ceiling height of 0 inches.…arrow_forward
- Suppose that a kitchen cabinet warehouse company would like to be able to predict the area of a customer’s kitchen using the number of cabinets and the kitchen ceiling height. To do so data is collected on the following variables from a random sample of customers: Area – area of the kitchen in square feet Height – ceiling height in the kitchen (from floor to ceiling) in inches Cabinets – number of cabinets in the kitchen Suppose that a multiple linear regression model was fit to the data and that the following output resulted: Coefficients: (Intercept)HeightCabinets Estimate-57.98771.2760.3393 Std. Error8.63820.26430.1302 t value -6.7134.8282.607 Pr(>|t|)2.75e-074.44e-050.0145 10 Question 10 This is not a form; we suggest that you use the browse mode and read all parts of the question carefully. Which of the following is the correct interpretation of the coefficient for Cabinets? For a kitchen with a given ceiling height, the average number of cabinets…arrow_forwardSuppose that a kitchen cabinet warehouse company would like to be able to predict the area of a customer’s kitchen using the number of cabinets and the kitchen ceiling height. To do so data is collected on the following variables from a random sample of customers: Area – area of the kitchen in square feet Height – ceiling height in the kitchen (from floor to ceiling) in inches Cabinets – number of cabinets in the kitchen Suppose that a multiple linear regression model was fit to the data and that the following output resulted: Coefficients: (Intercept)HeightCabinets Estimate-57.98771.2760.3393 Std. Error8.63820.26430.1302 t value -6.7134.8282.607 Pr(>|t|)2.75e-074.44e-050.0145 What is the predicted area of a kitchen with a height of 96 inches and 10 cabinets? Report your answer to 1 decimal place. square feetarrow_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_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: State the hypothesis for this study.arrow_forwardA sociologist was hired by a large city hospital to investigate the relationship between thenumber of unauthorized days that employees are absent per year and the distance (miles)between home and work for the employees. A sample of 10 employees was chosen, andthe following data were collected. a. Develop a scatter chart for these data. Does a linear relationship appear reasonable?Explain.b. Use the data to develop an estimated regression equation that could be used to predict thenumber of days absent given the distance to work. What is the estimated regression model?c. What is the 99 percent confidence interval for the regression parameter b1? Based onthis interval, what conclusion can you make about the hypotheses that the regressionparameter b1 is equal to zero?d. What is the 99 percent confidence interval for the regression parameter b0? Based onthis interval, what conclusion can you make about the hypotheses that the regressionparameter b0 is equal to zero?e. How much of the…arrow_forwardMark Price, the new productions manager for Speakers and Company, needs to find out which variable most affects the demand for their line of company speakers. He is uncertain whether the unit price of the product or the effects of increased marketing are the main drivers in sales and wants to use regression analysis to figure out which factor drives more demand for its particular market. Pertinent information was collected by an extensive marketing project that lasted over the past 12 years and was reduced to the data that follow: YEAR 1 2 3 4 5 6 7 B 9 10 11 12 UNIT SALES (THOUSANDS) 398 698 898 y bar 1,304 1,163 1,195 898 1,200 982 1,235 875 811 PRICE $ PER UNIT 283 209 213 220 209 200 220 209 230 213 216 243 ADVERTISING ($000) 621 821 1,200 1,405 1,210 1,304 875 1,200 691 875 691 691 a. Perform a regression analysis based on these data using Excel. Note: Negative values should be indicated by a minus sign. Round your answers to 4 decimal places. Price advertisingarrow_forward
- The St. Lucian Government is interested in predicting the number of weekly riders on the public buses using the following variables: • • • • Price of bus trips per weekThe population in the cityThe monthly income of ridersAverage rate to park your personal vehicle Determine the multiple regression equation for the data. What is the predicted value of the number of weekly riders if: price of bus trips per week = $24; population = $2,000,000; the monthly income of riders = $13,500; and average rate to park your personal vehicle = $150. Interpret the coefficient of determination.arrow_forwardThe operations manager of a musical instrument distributor feels that the demand for Bass Drums may be related to the number of television appearances by the popular rick group Green Shades during the previous month. The manager has collected the data shown in the following table. Demand for Bass Drums 3 6 7 5 10 8 Green Shades TV appearances 3 4 7 6 8 5 Develop the linear regression equation to forecast. Forecast demand for Bass Drums when Green Shades’ TV appearances are 10. Compute MSE and standard deviation for Problem 8.arrow_forwardMark Price, the new productions manager for Speakers and Company, needs to find out which variable most affects the demand for their line of stereo speakers. He is uncertain whether the unit price of the product or the effects of increased marketing are the main drivers in sales and wants to use regression analysis to figure out which factor drives more demand for its particular market. Pertinent information was collected by an extensive marketing project that lasted over the past 12 years and was reduced to the data that follow: YEAR 123456789 10 11 12 UNIT SALES (THOUSANDS) 396 696 896 1,285 1,155 1,186 896 1,118 985 1,334 926 820 PRICE $/UNIT 282 219 206 210 219 209 218 206 220 206 226 236 ADVERTISING ($000) 600 829 1,118 1,413 1,214 1,285 907 1,118 708 907 708 682 a. Perform a regression analysis based on these data using Excel. (Negative values should be indicated by a minus sign. Round your answers to 4 decimal places.)arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
Algebra and Trigonometry (MindTap Course List)AlgebraISBN:9781305071742Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage Learning
College AlgebraAlgebraISBN:9781305115545Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage Learning
Linear Algebra: A Modern IntroductionAlgebraISBN:9781285463247Author:David PoolePublisher:Cengage Learning
Glencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw Hill
Functions and Change: A Modeling Approach to Coll...AlgebraISBN:9781337111348Author:Bruce Crauder, Benny Evans, Alan NoellPublisher:Cengage Learning
Algebra and Trigonometry (MindTap Course List)
Algebra
ISBN:9781305071742
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:Cengage Learning
College Algebra
Algebra
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:Cengage Learning
Linear Algebra: A Modern Introduction
Algebra
ISBN:9781285463247
Author:David Poole
Publisher:Cengage Learning
Glencoe Algebra 1, Student Edition, 9780079039897...
Algebra
ISBN:9780079039897
Author:Carter
Publisher:McGraw Hill
Functions and Change: A Modeling Approach to Coll...
Algebra
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Cengage Learning
Correlation Vs Regression: Difference Between them with definition & Comparison Chart; Author: Key Differences;https://www.youtube.com/watch?v=Ou2QGSJVd0U;License: Standard YouTube License, CC-BY
Correlation and Regression: Concepts with Illustrative examples; Author: LEARN & APPLY : Lean and Six Sigma;https://www.youtube.com/watch?v=xTpHD5WLuoA;License: Standard YouTube License, CC-BY