EBK STATISTICS FOR BUSINESS & ECONOMICS
12th Edition
ISBN: 8220100460463
Author: Anderson
Publisher: CENGAGE L
expand_more
expand_more
format_list_bulleted
Concept explainers
Videos
Textbook Question
Chapter 15.2, Problem 4E
A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures.
ŷ = 25 + 10x1 + 8x2
where
x1 = inventory investment ($1000s)
x2 = advertising expenditures ($1000s)
y = sales ($1000s)
- a. Predict the sales resulting from a $15,000 investment in inventory and an advertising budget of $10,000.
- b. Interpret b1 and b2 in this estimated regression equation.
Expert Solution & Answer
Trending nowThis is a popular solution!
Students have asked these similar questions
eBook
A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures.
ŷ = 35 + 10x₁ + 6x2
where
x1 = = inventory investment ($1000s)
x2 =
advertising expenditures ($1000s)
y = sales ($1000s)
a. Predict the sales resulting from a $15,000 investment in inventory and an advertising budget of $10,000.
$
b. Interpret b₁ and be in this estimated regression equation.
b₁: Sales can be expected to - Select your answer by $10 for every dollar increase in
constant.
b2: Sales can be expected to - Select your answer - by $6 for every dollar increase in
constant.
- Select your answer -
- Select your answer -
✓ when
✓ when
- Select your answer -
- Select your answer -
✓ is held
✓ is held
A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures.
where
9-21+ 10x+7x2
X₁ inventory investment ($1,000s)
x2
advertising expenditures ($1,000s)
y=sales ($1,000s).
(a) Predict the sales (in dollars) resulting from a $14,000 investment in inventory and an advertising budget of $11,000.
$
(b) Interpret b, and by in this estimated regression equation.
Sales can be expected to increase by $
inventory investment is held constant.
for every dollar increase in inventory Investment when advertising expenditure is held constant. Sales can be expected to increase by $
ASK YOUR TEACHER
PRACTICE AN
for every dollar increase in advertising expenditure when
A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures.
ŷ = 25 + 10x₁ + 8x2
where
X1 inventory investment ($1,000s)
x2
advertising expenditures ($1,000s)
y =
sales ($1,000s).
(a) Predict the sales (in dollars) resulting from a $15,000 investment in inventory and an advertising budget of $10,000.
=
=
(b) Interpret b₁ and b₂ in this estimated regression equation.
1
2
Sales can be expected to increase by $
be expected to increase by $
for every dollar increase in inventory investment when advertising expenditure is held constant. Sales can
for every dollar increase in advertising expenditure when inventory investment is held constant.
Chapter 15 Solutions
EBK STATISTICS FOR BUSINESS & ECONOMICS
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 World rated four component characteristics for...Ch. 15.2 - The Cond Nast Traveler Gold List provides ratings...Ch. 15.2 - Waterskiing and wakeboarding are two popular...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 - Prob. 18ECh. 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 - The Wall Street Journal conducted a study of...Ch. 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 - Prob. 30ECh. 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 - Prob. 43ECh. 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
- Does Table 2 represent a linear function? If so, finda linear equation that models the data.arrow_forwardFor the revenue model in Exercise 10.206 and Exercise 10.210, explain what the x-intercepts mean to the backpack retailer.arrow_forwardDemand 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_forward
- 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_forwardNeurology The average weight of a male child’s brain is 970 grams at age 1 and 1270 grams at age 3. (a) Assuming that the relationship between brain weight y and age t is linear, write a linear model for the data. (b) What is the slope and what does it tell you about brain weight? (c) Use your model to estimate the average brain weight at age 2. (d) Use your school’s library, the Internet, or some other reference source to find the actual average brain weight at age 2. How close was your estimate? (e) (d) Do you think your model could be used to determine the average brain weight of an adult? Explain.arrow_forwardA shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures. ŷ = 25 + 12x, + 7x2 where X1 = inventory investment ($1,000s) X2 = advertising expenditures ($1,000s) y = sales ($1,000s). (a) Predict the sales (in dollars) resulting from a $15,000 investment in inventory and an advertising budget of $11,000. $ (b) Interpret b, and b, in this estimated regression equation. Sales can be expected to increase by $ for every dollar increase in inventory investment when advertising expenditure is held constant. Sales can be expected to increase by $ for every dollar increase in advertising expenditure when inventory investment is held constant.arrow_forward
- A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures. ý = 25 + 12x, + 7x2 where x, = inventory investment ($1,000s) x, = advertising expenditures ($1,000s) y = sales ($1,000s). (a) Predict the sales (in dollars) resulting from a $15,000 investment in inventory and an advertising budget of $11,000. $ (b) Interpret b, and b, in this estimated regression equation. Sales can be expected to increase by $ for every dollar increase in inventory investment when advertising expenditure is held constant. Sales can be expected to increase by $ for every dollar increase in advertising expenditure when inventory investment is held constant. B Tutorialarrow_forwardA shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures. ŷ = 25 + 12x, + 7x2 where X, = inventory investment ($1,000s) X, = advertising expenditures ($1,000s) y = sales ($1,000s). (a) Predict the sales (in dollars) resulting from a $15,000 investment in inventory and an advertising budget of $11,000. $ 282000 (b) Interpret b, and b, in this estimated regression equation. Sales can be expected to increase by $ 12000 for every dollar increase in inventory investment when advertising expenditure is held constant. Sales can be expected to increase by $ 7000 x for every dollar increase in advertising expenditure when inventory investment is held constant.arrow_forwardA shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures. ŷ = 21 + 10x, + 7x2 %D where X1 inventory investment ($1,000s) advertising expenditures ($1,000s) X2 sales ($1,000s). y = (a) Predict the sales (in dollars) resulting from a $15,000 investment in inventory and an advertising budget of $10,000. (b) Interpret b1 and b, in this estimated regression equation. 2. Sales can be expected to increase by $ for every dollar increase in inventory investment when advertising expenditure is held constant. Sales can be expected to increase by $ for every dollar increase in advertising expenditure when inventory investment is held constant.arrow_forward
- A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures. ŷ = 21 + 10x, + 8x2 where x, = inventory investment ($1,000s) X2 = advertising expenditures ($1,000s) y = sales ($1,000s). (a) Predict the sales (in dollars) resulting from a $15,000 investment in inventory and an advertising budget of $11,000. %24 (b) Interpret b, and b, in this estimated regression equation. Sales can be expected to increase by $ for every dollar increase in inventory investment when advertising expenditure is held constant. Sales can be expected to increase by $ for every dollar increase in advertising expenditure when inventory investment is held constant.arrow_forwarda. Predict the sales resulting from a $15,000 investment in inventory and an advertising budget of $10,000.arrow_forwardSpring is a peak time for selling houses. The file SpringHouses contains the selling price, number of bathrooms, square footage, and number of bedrooms of 26 homes sold in Ft. Thomas, Kentucky, in spring 2018 (realtor.com website) Click on the datafile logo to reference the data. DATA file a. The Excel output for the estimated regression equation that can be used to predict the selling price given the number of bathrooms, square footage, and number of bedrooms in the house: SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression statistics Regression Residual Total Multiple R R Square ANOVA Adjusted R Square Standard Error Observations 0.7429 0.5519 0.4907 61948.6931 Regression statistics Regression Residual Total df Intercept Sq Ft Beds Lower 95% 0.9353 -145129.5298 Intercept Baths 0.9528 -49383.5243 0.0180 Sq Ft Beds 0.0326 Does the estimated regression equation provide a good fit to the data? Explain. Hint: If R is greater than 45%, the…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
Intermediate AlgebraAlgebraISBN:9781285195728Author:Jerome E. Kaufmann, Karen L. SchwittersPublisher:Cengage Learning
Big Ideas Math A Bridge To Success Algebra 1: Stu...AlgebraISBN:9781680331141Author:HOUGHTON MIFFLIN HARCOURTPublisher:Houghton Mifflin Harcourt
Trigonometry (MindTap Course List)TrigonometryISBN:9781337278461Author:Ron LarsonPublisher:Cengage Learning
Algebra and Trigonometry (MindTap Course List)AlgebraISBN:9781305071742Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher: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
Intermediate Algebra
Algebra
ISBN:9781285195728
Author:Jerome E. Kaufmann, Karen L. Schwitters
Publisher:Cengage Learning
Big Ideas Math A Bridge To Success Algebra 1: Stu...
Algebra
ISBN:9781680331141
Author:HOUGHTON MIFFLIN HARCOURT
Publisher:Houghton Mifflin Harcourt
Trigonometry (MindTap Course List)
Trigonometry
ISBN:9781337278461
Author:Ron Larson
Publisher:Cengage Learning
Algebra and Trigonometry (MindTap Course List)
Algebra
ISBN:9781305071742
Author:James Stewart, Lothar Redlin, Saleem Watson
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