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12.14. The Great Northwest Outdoor Company is a catalog sales operation that specializes in outdoor recreational clothing. Demand for its items is very seasonal, peaking during the holiday season and during the spring. It has accumulated the following data for orders per "season" (quarter) during the past five years: Orders (1000s) Quarter/Year 1 3 4 January-March 18.6 18.1 22.4 23.2 24.5 April-June 23.5 24.7 28.8 27.6 31.0 July-September 20.4 19.5 21.0 24.4 23.7 October-December 41.9 46.3 45.5 47.1 52.8 a. Develop a seasonally adjusted forecast model for these order bae data. Forecast demand for each quarter for year 6 (using a linear trend line forecast estimate for orders in year 6). b. Develop a separate linear trend line forecast for each of the four seasons and forecast each season for year 6. c. Which of the two approaches used in parts (a) and (b) appear mort accurate? Use MAD to yerify Your selection.

12.14. The Great Northwest Outdoor Company is a catalog sales operation that specializes in outdoor recreational clothing. Demand for its items is very seasonal, peaking during the holiday season and during the spring. It has accumulated the following data for orders per "season" (quarter) during the past five years: Orders (1000s) Quarter/Year 1 3 4 January-March 18.6 18.1 22.4 23.2 24.5 April-June 23.5 24.7 28.8 27.6 31.0 July-September 20.4 19.5 21.0 24.4 23.7 October-December 41.9 46.3 45.5 47.1 52.8 a. Develop a seasonally adjusted forecast model for these order bae data. Forecast demand for each quarter for year 6 (using a linear trend line forecast estimate for orders in year 6). b. Develop a separate linear trend line forecast for each of the four seasons and forecast each season for year 6. c. Which of the two approaches used in parts (a) and (b) appear mort accurate? Use MAD to yerify Your selection.

Practical Management Science
Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter2: Introduction To Spreadsheet Modeling
Section: Chapter Questions
Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...
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12.14. The Great Northwest Outdoor Company is a catalog sales operation that specializes in outdoor recreational clothing. Demand for its items is very seasonal, peaking during the holiday season and during the spring. It has accumulated the following data for orders per "season" (quarter) during the past five years: Orders (1000s) Quarter/Year 1 3 4 January-March 18.6 18.1 22.4 23.2 24.5 April-June 23.5 24.7 28.8 27.6 31.0 July-September 20.4 19.5 21.0 24.4 23.7o October-December 41.9 46.3 45.5 47.1 52.8 col ban a. Develop a seasonally adjusted forecast model for these order bas art data. Forecast demand for each quarter for year 6 (using a linear trend line forecast estimate for orders in year 6). b. Develop a separate linear trend line forecast for each of the four seasons and forecast each season for year 6. c. Which of the two approaches used in parts (a) and (b) appear to be the most accurate? Use MAD to verify your selection.
Transcribed Image Text:12.14. The Great Northwest Outdoor Company is a catalog sales operation that specializes in outdoor recreational clothing. Demand for its items is very seasonal, peaking during the holiday season and during the spring. It has accumulated the following data for orders per "season" (quarter) during the past five years: Orders (1000s) Quarter/Year 1 3 4 January-March 18.6 18.1 22.4 23.2 24.5 April-June 23.5 24.7 28.8 27.6 31.0 July-September 20.4 19.5 21.0 24.4 23.7o October-December 41.9 46.3 45.5 47.1 52.8 col ban a. Develop a seasonally adjusted forecast model for these order bas art data. Forecast demand for each quarter for year 6 (using a linear trend line forecast estimate for orders in year 6). b. Develop a separate linear trend line forecast for each of the four seasons and forecast each season for year 6. c. Which of the two approaches used in parts (a) and (b) appear to be the most accurate? Use MAD to verify your selection.
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