MyLab Operations Management with Pearson eText -- Access Card -- for Operations Management: Processes and Supply Chains
11th Edition
ISBN: 9780133885583
Author: Lee J. Krajewski, Manoj K. Malhotra, Larry P. Ritzman
Publisher: PEARSON
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Chapter 8, Problem 1P
Demand for oil changes at Garcia’s Garage has been as follows:
- Use simple linear regression analysis to develop a
forecasting model for monthly demand. In this application, the dependent variable, Y, is monthly demand and the independent variable, X, is the month. For January, let - Use time model to forecast demand for September, October, and November. Here,
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3) Seasonality: The following data represent dinner sales at a busy restaurant. Use linear
regression to predict sales for each day of week 5 and the total sales for week 5. Estimate the
percentage of weekly sales that occur over the weekend (include Friday, Saturday, and
Sunday). Finally, determine which days of the week are increasing and decreasing in sales, using
the slopes of the LR lines.
Week
Mon
Wed
Fri
Sat
Sun
Tue
177
170
Thu
190
Total
270
152
180
321
386
166
218
203
402
427
167
333
357
229
3
158
170
170
205
163
173
158
225
349
433
212
a) Graph the seasonal data and attach the graph to this page.
b) Determine the slope for each day of the week.
Mon
Tue
Wed
Thu
Fri
Sat
Sun
Total
Slope
c) Estimate the percentage of weekend sales in week 5:
d) For which day are sales increasing the fastest?
e) For which day are sales decreasing the fastest?
Demand for oil changes at Garcia's Garage has been as follows:
Month
January
February
March
April
May
June
July
August
Number of Oil Changes
38
55
56
60
58
01
70
52
a. Use simple linear regression analysis to develop a forecasting model for monthly demand. In this application, the dependent variable, Y, is monthly demand and the independent variable, X, is the
month. For January, let X=1; for February, let X 2; and so on.
The forecasting model is given by the equation Y=X (Enter your responses rounded to two decimal places)
Demand for oil changes at Garcia's Garage has been as follows:
Number of Oil Changes
January
44
February
49
March
66
IT
April
59
May
53
June
58
59
63
Month
July
August
a. Use simple linear regression analysis to develop a forecasting model for monthly demand. In this application, the dependent variable, Y, is monthly demand and the independent variable, X, is the month. For Janu
The forecasting model is given by the equation Y=+x. (Enter your responses rounded to two decimal places)
J
Show Transcribed Text
>. Use the model to forecast demand for September, October, and November. Here, X=9, 10, and 11, respectively. (Enter your responses rounded to two decimal places.)
Forecast for the number of
Oil Changes
Show Transcribed Text
Month
September
October
November
can you do all the parts please corrrect
Chapter 8 Solutions
MyLab Operations Management with Pearson eText -- Access Card -- for Operations Management: Processes and Supply Chains
Ch. 8 - Figure 8.9 shows summer air visibility...Ch. 8 - Kay and Michael Passe publish What‘s...Ch. 8 - Demand for oil changes at Garcia’s Garage has...Ch. 8 - Prob. 2PCh. 8 - Ohio Swiss Milk Products manufactures and...Ch. 8 - A manufacturing firm has developed a skills test,...Ch. 8 - The materials handling manager of a manufacturing...Ch. 8 - Marianne Kramer, the owner of Handy Man Rentals,...Ch. 8 - Sales for the past 12 months at Computer Success...Ch. 8 - Bradley’s Copiers sells and repairs photocopy...
Ch. 8 - Consider the sales data for Computer Success given...Ch. 8 - A convenience store recently started to carry a...Ch. 8 - Community Federal Bank in Dothan, Alabama,...Ch. 8 - The number of heart surgeries performed at...Ch. 8 - The following data are for calculator sales in...Ch. 8 - Prob. 14PCh. 8 - Forrest and Dan make boxes of chocolates for which...Ch. 8 - The manager of Alaina’s Garden Center must make...Ch. 8 - The manager of a utility company in the Texas...Ch. 8 - Franklin Tooling, Inc., manufactures specialty...Ch. 8 - Create an Excel spreadsheet on your own that can...Ch. 8 - Prob. 20PCh. 8 - Using the data in Problem 20 and the Time-Series...Ch. 8 - Prob. 22PCh. 8 - Cannister, Inc., specializes in the manufacture of...Ch. 8 - The Midwest Computer Company serves a large number...Ch. 8 - A certain food item at P=0.20 (with a combination...Ch. 8 - Prob. 26PCh. 8 - Prob. 27PCh. 8 - A manufacturing firm seeks to develop a better...Ch. 8 - How much does the forecasting process at Deckers...Ch. 8 - Prob. 2VCCh. 8 - What factors make forecasting at Deckers...Ch. 8 - Prob. 4VCCh. 8 - Prob. 5VCCh. 8 - Comment on the forecasting system being used by...Ch. 8 - Develop your own forecast for bow rakes for each...
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