Bundle: Statistics for Business & Economics, Loose-Leaf Version, 13th + MindTap Business Statistics with XLSTAT, 1 term (6 months) Printed Access Card
13th Edition
ISBN: 9781337148092
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: Cengage Learning
expand_more
expand_more
format_list_bulleted
Concept explainers
Videos
Textbook Question
Chapter 15.6, Problem 29E
In exercise 5, the owner of Showtime Movie Theaters, Inc., used multiple
ŷ = 83.2 + 2.29x1 + 1.30x2
- a. What is the gross revenue expected for a week when $3500 is spent on television advertising (x1 = 3.5) and $1800 is spent on newspaper advertising (x2 = 1.8)?
- b. Provide a 95% confidence interval for the mean revenue of all weeks with the expenditures listed in part (a).
- c. Provide a 95% prediction interval for next week’s revenue, assuming that the advertising expenditures will be allocated as in part (a).
Expert Solution & Answer
Trending nowThis is a popular solution!
Students have asked these similar questions
A marketing consultant created a linear regression model to predict the number of units sold by a client based on the amount of money spent on marketing by the client. Which of the following is the best
graphic to use to evaluate the appropriateness of the model?
The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x 1) and newspaper advertising (x 2). The estimated regression equation was
ŷ = 87.2 + 1.39 x 1 + 0.54 x 2
Weekly Gross Revenue ($1000s)
Televison Advertising ($1000s)
Newspaper Advertising ($1000s)
97
6
2.5
91
2
2
96
5
2.5
93
2.5
3.5
95
4
4.3
94
4.5
2.3
94
3.5
4.2
94
4
2.5
The computer solution provided SST = 23.5 and SSR = 22.437.
Compute R 2 and R a 2 (to 3 decimals).
R 2
R a 2
A real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently
sold homes in the space, the following variables are used in a multiple regression model.
y = sales price (in thousands of dollars)
x₁ =
total floor area (in square feet)
x₂ =
number of bedrooms
x3 distance to nearest high school (in miles)
=
The estimated model is as follows.
=76+0.098x₁ +16x₂ - 8x3
Answer the questions below for the interpretation of the coefficient of X₂ in this model.
(a) Holding the other variables fixed, what is the average change in sales price for each
additional bedroom in a house?
dollars
(b) Is this change an increase or a decrease?
O increase
O decrease
X
Chapter 15 Solutions
Bundle: Statistics for Business & Economics, Loose-Leaf Version, 13th + MindTap Business Statistics with XLSTAT, 1 term (6 months) Printed Access Card
Ch. 15.2 - The estimated regression equation for a model...Ch. 15.2 - Consider the following data for a dependent...Ch. 15.2 - In a regression analysis involving 30...Ch. 15.2 - A shoe store developed the following estimated...Ch. 15.2 - The owner of Showtime Movie Theaters, Inc., would...Ch. 15.2 - The National Football League (NFL) records a...Ch. 15.2 - PC Magazine provided ratings for several...Ch. 15.2 - The Cond Nast Traveler Gold List provides ratings...Ch. 15.2 - The Professional Golfers Association (PGA)...Ch. 15.2 - Prob. 10E
Ch. 15.3 - In exercise 1, the following estimated regression...Ch. 15.3 - Prob. 12ECh. 15.3 - In exercise 3, the following estimated regression...Ch. 15.3 - In exercise 4, the following estimated regression...Ch. 15.3 - In exercise 5, the owner of Showtime Movie...Ch. 15.3 - In exercise 6, data were given on the average...Ch. 15.3 - Prob. 17ECh. 15.3 - Refer to exercise 10, where Major League Baseball...Ch. 15.5 - In exercise 1, the following estimated regression...Ch. 15.5 - Refer to the data presented in exercise 2. The...Ch. 15.5 - The following estimated regression equation was...Ch. 15.5 - In exercise 4, the following estimated regression...Ch. 15.5 - Prob. 23ECh. 15.5 - Prob. 24ECh. 15.5 - The Cond Nast Traveler Gold List for 2012 provided...Ch. 15.5 - In exercise 10, data showing the values of several...Ch. 15.6 - In exercise 1, the following estimated regression...Ch. 15.6 - Refer to the data in exercise 2. The estimated...Ch. 15.6 - In exercise 5, the owner of Showtime Movie...Ch. 15.6 - In exercise 24, an estimated regression equation...Ch. 15.6 - The American Association of Individual Investors...Ch. 15.7 - Consider a regression study involving a dependent...Ch. 15.7 - Consider a regression study involving a dependent...Ch. 15.7 - Management proposed the following regression model...Ch. 15.7 - Refer to the Johnson Filtration problem introduced...Ch. 15.7 - This problem is an extension of the situation...Ch. 15.7 - The Consumer Reports Restaurant Customer...Ch. 15.7 - A 10-year study conducted by the American Heart...Ch. 15.8 - Data for two variables, x and y, follow. xi 1 2 3...Ch. 15.8 - Data for two variables, x and y, follow. xi 22 24...Ch. 15.8 - Exercise 5 gave the following data on weekly gross...Ch. 15.8 - The following data show the curb weight,...Ch. 15.8 - The Ladies Professional Golfers Association (LPGA)...Ch. 15.9 - Refer to the Simmons Stores example introduced in...Ch. 15.9 - In Table 15.12 we provided estimates of the...Ch. 15.9 - Community Bank would like to increase the number...Ch. 15.9 - Over the past few years the percentage of students...Ch. 15.9 - The Tire Rack maintains an independent consumer...Ch. 15 - The admissions officer for Clearwater College...Ch. 15 - The personnel director for Electronics Associates...Ch. 15 - A partial computer output from a regression...Ch. 15 - Recall that in exercise 49, the admissions officer...Ch. 15 - Recall that in exercise 50 the personnel director...Ch. 15 - The Tire Rack, Americas leading online distributor...Ch. 15 - The Department of Energy and the U.S....Ch. 15 - A portion of a data set containing information for...Ch. 15 - Fortune magazine publishes an annual list of the...Ch. 15 - Consumer Research, Inc., is an independent agency...Ch. 15 - Matt Kenseth won the 2012 Daytona 500, the most...Ch. 15 - Finding the Best Car Value When trying to decide...
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
- After interviewing salespersons at Harley Davidson dealerships, a researcher has created a linear regression line to explain the relationship between a Harley Davidson motorcycle's age (x) and price (y). The regression has an R² = 87.7%. Write a sentence summarizing what R² says about this regression. The age of the motorcycle explains 12.3% of the variation in price. The age of the motorcycle explains 9.36% of the variation in price. The age of the motorcycle explains 87.7% of the variation in price. The price of the motorcycle explains 12.3% of the variation in age. The price of the motorcycle explains 87.7% of the variation in age.arrow_forwardThe owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x 1) and newspaper advertising (x 2). The estimated regression equation was Weekly Gross Revenue ($1000s) Televison Advertising ($1000s) Newspaper Advertising ($1000s) 97 6 1.5 91 3 2 95 5 2.5 93 3.5 2.5 96 4 4.3 94 4.5 2.3 95 3.5 4.2 95 4 3.5 ŷ = 82.5 + 2.01 x 1 + 1.26 x 2The computer solution provided SST = 24 and SSR = 22.876. Compute R 2 and R a 2 (to 3 decimals). R 2 R a 2 When television advertising was the only independent variable, R 2 = 0.551 and R a 2 = 0.476. Are the multiple regression analysis results preferable?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. What proportion of variation in the number of complaints can be explained by hourly wages? From the results shown above, write the regression equation If wages were increased by $1.00, what is the expected effect on the number of complaints received per employee?arrow_forward
- The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1) and newspaper advertising (*2). Weekly Gross Television Newspaper Revenue Advertising Advertising ($1000s) ($1000s) ($1000s) 96 6.0 2.5 90 2.0 3.0 96 5.0 2.5 92 3.5 2.5 96 4.0 3.3 95 3.5 3.3 94 2.5 4.2 95 4.0 3.5 The estimated regression equation was ŷ = 79.4 + 1.94x1 + 2.40x2. The computer solution provided SST = 33.5 and SSR = 29.283. a. Compute and interpret R2 and R. (to 3 decimals). R2 = R = b. When television advertising was the only independent variable, R = 0.653 and R = 0.595. Do you prefer the multiple regression results? Explain. No, because less variability is explained when both independent variables are usedarrow_forwardA professor was doing a study on the relationship between the amount of television a person watches per day (in hours) and the person's IQ. The professor found that a linear relationship exists between the two variables and determined the equation of the least squares regression line to be ŷ = -0.4x + 107. Interpret the slope. [ Select ] ( Select ] As a person's IQ increases by 1 point, the amount the person spends watching television increases by 0.4 hours, on average. As a person's IQ increases by 1 point, the amount the person spends watching television decreases by 0.4 hours, on average. As the amount of time a person watches TV increases by 1 hour, the person's IQ is expected to increase by 0.4 points, on average. As the amount of time a person watches TV increases by 1 hour, the person's IQ is expected to decrease by 0.4 points, on average. Predict the IQ of a person who watches 3 hours of television per day. [ Select] Dexter spends 4 hours watching television per day and has an…arrow_forwardA real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the space, the following variables are used in a multiple regression model. y sales price (in thousands of dollars) x₁ = total floor area (in square feet) X₂= number of bedrooms x3² distance to nearest high school (in miles) The estimated model is as follows. y=121 +0.083x₁ +23x₂ - 4x3 Answer the questions below for the interpretation of the coefficient of x₁ in this model. (a) Holding the other variables fixed, what is the average change in sales price for each 100-square-foot increase in floor area? dollars (b) Is this change an increase or a decrease? increase decrease X Śarrow_forward
- A financial website reported the beta value for a certain company was 0.86. Betas for individual stocks are determined by simple linear regression. The dependent variable is the total return for the stock, and the independent variable is the total return for the stock market, such as the return of a market index. The slope of this regression equation is referred to as the stock's beta. Many financial analysts prefer to measure the risk of a stock by computing the stock's beta value. Suppose the following data show the monthly percentage returns for the market index and the company for a recent year. Month Market Index% Return Company% Return August -3 4 September 8 7 October 0 1 November -2 1 December -5 0 January 0 0 February 7 7 March 0 -2 April 2 0 May -5 -1 a. Develop the least squares estimated regression equation. (Let x = Market Index % Return (as a %), and let y = Company % Return (as a %). Round your numerical values to four decimal places.)arrow_forwardThe owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1) and newspaper advertising (x2). Values of y, x1, and x2 are expressed in thousands of dollars. Weekly Gross Television Newspaper Revenue Advertising Advertising 96 5.0 1.5 90 2.0 2.0 95 4.0 1.5 92 2.5 2.5 95 3.0 3.3 94 3.5 2.3 94 2.5 4.2 94 3.0 2.5 a. What is the gross revenue expected for a week where $3,500 is spent on television (x1 =3.5) and $1,800 is spent on newspaper advertising (x2= 1.8)(to 3 decimals)? b. Provide a 95 prediction interval for next week's revenue, assuming that the advertising expenditures will be allocated as in part (a) (to 2 decimals). (_____ thousand, ______ thousand)arrow_forwardFind the degrees of freedom in a regression model with an intercept term that has 88 observations and 7 explanatory variables.arrow_forward
- In a fisheries researcher's experiment, the correlation between the number of eggs in the nest and the number of viable (surviving) eggs for a sample of nests is r = 0.67. The equation of the regression line for number of viable eggs y versus number of eggs in the nest x is y = 0.72x + 17.07. For a nest with 140 eggs, what is the predicted number of viable eggs?arrow_forwardA FIFA World Cup football is dropped from 35 different heights (in cm) and the height of the bounce is recorded (in cm.) The regression analysis gives the model bounce = -0.1 +0.70 drop. Predict the height of the bounce if dropped from 64 cm. 44.7 cm 44.8 cm 64.6 cm 91.57 cm 44.9 cmarrow_forwardThe owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (1) as a function of television advertising (Z1) and newspaper advertising (). Weekly Gross Television Newspaper Revenue Advertising Advertising ($1000s) ($1000s) ($1000s) 97 6.0 1.5 90 2.0 3.0 96 5.0 1.5 92 2.5 2.5 95 4.0 4.3 94 3.5 3.3 94 2.5 5.2 95 4.0 3.5 The estimated regression equation was y = 86.0 + 1.87z1 +0.71r2 The computer solution provided SST- 34.9 and SSR 32.700 a. Compute and interpret R and R: (to 3 decimals). R R b. When television advertising was the only independent variable, R = 0.653 and Ra = 0.595, Do you prefer the multiple regression results? Explain. Select your answer-arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
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
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