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Business Forecasting 9th Edition by John Hanke, Dean Wichern
Edition 9ISBN: 978-0132301206Business Forecasting 9th Edition by John Hanke, Dean Wichern
Edition 9ISBN: 978-0132301206 Exercise 2
ACE MANUFACTURING
Ace Manufacturing Company employs several thousand people in the manufacture of keyboards, equipment cases, and cables for the small-computer industry. The president of Ace has recently become concerned with the absentee rate among the company's employees and has asked the personnel department to look into this matter. Personnel realizes that an effective method of forecasting absenteeism would greatly strengthen its ability to plan properly. Bill McGone, the personnel director, decides to take a look at a few personnel folders in an attempt to size up the problem. He decides to randomly select 15 folders and record the number of absent days during the past fiscal year, along with employee age. After reading an article in a recent personnel journal, he believes that age may have a significant effect on absenteeism. If he finds that age and absent days show a good correlation in his small sample, he intends to take a sample of 200 or 300 folders and formulate a good prediction equation. The following table contains the data values collected in the initial sample. The number of absent days during the past fiscal year is represented by Y , while X represents employee age.
What is the forecasting equation for absent days using age as a predictor variable?
Ace Manufacturing Company employs several thousand people in the manufacture of keyboards, equipment cases, and cables for the small-computer industry. The president of Ace has recently become concerned with the absentee rate among the company's employees and has asked the personnel department to look into this matter. Personnel realizes that an effective method of forecasting absenteeism would greatly strengthen its ability to plan properly. Bill McGone, the personnel director, decides to take a look at a few personnel folders in an attempt to size up the problem. He decides to randomly select 15 folders and record the number of absent days during the past fiscal year, along with employee age. After reading an article in a recent personnel journal, he believes that age may have a significant effect on absenteeism. If he finds that age and absent days show a good correlation in his small sample, he intends to take a sample of 200 or 300 folders and formulate a good prediction equation. The following table contains the data values collected in the initial sample. The number of absent days during the past fiscal year is represented by Y , while X represents employee age.
What is the forecasting equation for absent days using age as a predictor variable?
Explanation
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Obtain the forecasting equation for abse...
Business Forecasting 9th Edition by John Hanke, Dean Wichern
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