Operations Management
11th Edition
ISBN: 9780132921145
Author: Jay Heizer
Publisher: PEARSON
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Textbook Question
Chapter 4, Problem 35P
Question
•• 4.35 Rhonda Clark, a Slippery Rock, Pennsylvania, real estate developer, has devised a regression model to help determine residential housing prices in northwestern Pennsylvania. The model was developed using recent sales in a particular neighborhood. The price (Y) of the house is based on the size (square foot-age = X) of the house. The model is:
The coefficient of correlation for the model is 0.63.
- a. Use the model to predict the selling price of a house that is 1,860 square feet.
- b. An 1,360-square-foot house recently sold for $95,000. Explain why this is not what the model predicted.
- c. If you were going to use multiple regression to develop such a model, what other quantitative variables might you include?
- d. What is the value of the coefficient of determination in this problem?
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Question 3
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(8 points) Infoworks is a large computer discount store that sells computers and ancillary equipment and software in the town where a State University is located. Infoworks has collected historical data on computer sales and printer sales for the past 10 years, as follows:
Develop a linear regression model relating printer sales to computer sales in order to forecast printer demand in year 11 if 1,300 computers are sold.
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Develop an exponential smoothing model with α = .30 to forecast printer demand in year 11.
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QUESTION 4
The following table shows the weights and prices of some whole rotisserie chickens at Price Mart.
Make a scatterplot with weight on the x-axis and cost on the y-axis. Include the regression line on your scatter
Find the numerical value for the correlation between weight and Explain what the sign of the correlation
What is the equation of the best-fit straight line, using weight as the predictor (x) and cost as the response (y).
What does the slope of the regression line tell us?
Find and interpret the coefficient of determination using the original
Weight (lb.)
Price
2.8
$3.92
3.7
$4.70
2.9
$4.41
4.2
$5.38
5.3
$6.84
4.7
$5.99
Chapter 4 Solutions
Operations Management
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