Pearson eText Principles of Operations Management: Sustainability and Supply Chain Management -- Instant Access (Pearson+)
11th Edition
ISBN: 9780135639221
Author: Jay Heizer, Barry Render
Publisher: PEARSON+
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Chapter 4, Problem 55P
a)
Summary Introduction
To
b)
Summary Introduction
To forecast: The job performance index of an applicant who had a 2.5 GPA and 70 score.
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The following multiple regression printout can be used to predict a person's height (in inches) given his or her shoe size and gender, where gender = 1 for males and 0 for females.
Regression Analysis: Height Versus Shoe Size,
Gender
Coefficients
Term
Coef
Constant
55.28
SE Coef
1.04
T-Value
P-Value
Shoe Size
0.105
Gender
0.268
0.12
0.489
53.1
0.875
0.000
0.000
0.548
0.000
(a) The dependent variable in this regression is which of the following?
height
gender
shoe size
constant
(b)
What is the regression coefficient of shoe size?
(c) What is the regression coefficient of gender?
The following multiple regression model was developedto predict job performance as measured by a company jobperformance evaluation index based on a preemployment testscore and college grade point average (GPA):Wherey = 35 + 20x1 + 50x2y = job performance evaluation indexx 1 =preemployment test scorex2 =college GPAa) Forecast the job performance index for an applicant who hada 3.0 GPA and scored 80 on the preemployment test. b) Forecast the job performance index for an applicant who hada 2.5 GPA and scored 70 on the preemployment test.
what do the standardized regression weights or coefficients tell you about the ability of the predictors to predict the dependent variable?
Chapter 4 Solutions
Pearson eText Principles of Operations Management: Sustainability and Supply Chain Management -- Instant Access (Pearson+)
Ch. 4 - Ethical Dilemma We live in a society obsessed with...Ch. 4 - What is a qualitative forecasting model, and when...Ch. 4 - Identify and briefly describe the two general...Ch. 4 - Identify the three forecasting time horizons....Ch. 4 - Briefly describe the steps that are used to...Ch. 4 - A skeptical manager asks what medium-range...Ch. 4 - Explain why such forecasting devices as moving...Ch. 4 - What is the basic difference between a weighted...Ch. 4 - What three methods are used to determine the...Ch. 4 - Research and briefly describe the Delphi...
Ch. 4 - What is the primary difference between a...Ch. 4 - Define time series.Ch. 4 - What effect does the value of the smoothing...Ch. 4 - Explain the value of seasonal indices in...Ch. 4 - Prob. 14DQCh. 4 - In your own words, explain adaptive forecasting.Ch. 4 - Prob. 16DQCh. 4 - Explain, in your own words, the meaning of the...Ch. 4 - Prob. 18DQCh. 4 - Give examples of industries that are affected by...Ch. 4 - Prob. 20DQCh. 4 - Prob. 21DQCh. 4 - CEO John Goodale, at Southern Illinois Power and...Ch. 4 - The following gives the number of pints of type B...Ch. 4 - a) Plot the above data on a graph. Do you observe...Ch. 4 - Refer to Problem 4.2. Develop a forecast for years...Ch. 4 - A check-processing center uses exponential...Ch. 4 - The Carbondale Hospital is considering the...Ch. 4 - The monthly sales for Yazici Batteries, Inc., were...Ch. 4 - Prob. 7PCh. 4 - Daily high temperatures in St. Louis for the last...Ch. 4 - Lenovo uses the ZX-81 chip in some of its laptop...Ch. 4 - Data collected on the yearly registrations for a...Ch. 4 - Use exponential smoothing with a smoothing...Ch. 4 - Prob. 12PCh. 4 - At you can see in the following table, demand for...Ch. 4 - Prob. 14PCh. 4 - Refer to Solved Problem 4.1 on page 144. a) Use a...Ch. 4 - Prob. 16PCh. 4 - Prob. 17PCh. 4 - Prob. 18PCh. 4 - Income at the architectural firm Spraggins and...Ch. 4 - Resolve Problem 4.19 with = .1 and =.8. Using...Ch. 4 - Prob. 21PCh. 4 - Refer to Problem 4.21. Complete the trend-adjusted...Ch. 4 - Prob. 23PCh. 4 - The following gives the number of accidents that...Ch. 4 - In the past, Peter Kelles tire dealership in Baton...Ch. 4 - George Kyparisis owns a company that manufactures...Ch. 4 - Attendance at Orlandos newest Disneylike...Ch. 4 - Prob. 28PCh. 4 - The number of disk drives (in millions) made at a...Ch. 4 - Prob. 30PCh. 4 - Emergency calls to the 911 system of Durham, North...Ch. 4 - Using the 911 call data in Problem 4.31, forecast...Ch. 4 - Storrs Cycles has just started selling the new...Ch. 4 - Prob. 35PCh. 4 - Prob. 36PCh. 4 - Prob. 37PCh. 4 - Prob. 38PCh. 4 - Prob. 39PCh. 4 - Prob. 40PCh. 4 - Prob. 41PCh. 4 - Prob. 42PCh. 4 - Mark Gershon, owner of a musical instrument...Ch. 4 - Prob. 44PCh. 4 - Cafe Michigans manager, Gary Stark, suspects that...Ch. 4 - Prob. 46PCh. 4 - The number of auto accidents in Athens, Ohio, is...Ch. 4 - Rhonda Clark, a Slippery Rock, Pennsylvania, real...Ch. 4 - Accountants at the Tucson firm, Larry Youdelman,...Ch. 4 - Prob. 50PCh. 4 - Using the data in Problem 4.30, apply linear...Ch. 4 - Bus and subway ridership for the summer months in...Ch. 4 - Prob. 53PCh. 4 - Dave Fletcher, the general manager of North...Ch. 4 - Prob. 55PCh. 4 - Prob. 56PCh. 4 - Prob. 57PCh. 4 - Sales of tablet computers at Ted Glickmans...Ch. 4 - The following are monthly actual and forecast...Ch. 4 - Prob. 1CSCh. 4 - Prob. 2CSCh. 4 - Prob. 3CSCh. 4 - Prob. 1.1VCCh. 4 - Prob. 1.2VCCh. 4 - Using Perezs multiple-regression model, what would...Ch. 4 - Prob. 1.4VCCh. 4 - Prob. 2.1VCCh. 4 - Prob. 2.2VCCh. 4 - Prob. 2.3VCCh. 4 - Prob. 2.4VCCh. 4 - Prob. 2.5VC
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- The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?arrow_forwardThe management of a technology company is trying to determine the variable that best explains the variation of employee salaries using a sample of 52 full-time employees; see the file P13_08.xlsx. Estimate simple linear regression equations to identify which of the following has the strongest linear relationship with annual salary: the employees gender, age, number of years of relevant work experience prior to employment at the company, number of years of employment at the company, or number of years of post secondary education. Provide support for your conclusion.arrow_forwardDo the sales prices of houses in a given community vary systematically with their sizes (as measured in square feet)? Answer this question by estimating a simple regression equation where the sales price of the house is the dependent variable, and the size of the house is the explanatory variable. Use the sample data given in P13_06.xlsx. Interpret your estimated equation, the associated R-square value, and the associated standard error of estimate.arrow_forward
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