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##### Complete problems 4.1, 4.3, 4.5, 4.25, and 4.27 in...

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Complete problems 4.1, 4.3, 4.5, 4.25, and 4.27 in the textbook. Submit one Excel file. Put each problem result on a separate sheet in your file. 4.1 The following gives the number of pints of type B blood used at Woodlawn Hospital in the past 6 weeks: WEEK OF PINTS USED August 31 360 September 7 389 September 14 410 September 21 381 September 28 368 October 5 374 a) Forecast the demand for the week of October 12 using a 3-week moving average. b) Use a 3-week weighted moving average, with weights of .1, .3, and .6, using .6 for the most recent week. Forecast demand for the week of October 12. c) Compute the forecast for the week of October 12 using exponential smoothing with a forecast for August 31 of 360 and a 5 .2 4.2 YEAR 1 2 3 4 5 6 7 8 9 10 11 DEMAND 7 9 5 9 13 8 12 13 9 11 7 4.3 Refer to Problem 4.2. Develop a forecast for years 2 through 12 using exponential smoothing with a 5 .4 and a forecast for year 1 of 6. Plot your new forecast on a graph with the actual data and the naive forecast. Based on a visual inspection, which forecast is better? 4.5 The Carbondale Hospital is considering the purchase of a new ambulance. The decision will rest partly on the anticipated mileage to be driven next year. The miles driven during the past 5 years are as follows: YEAR MILEAGE 1 3,000 2 4,000 3 3,400 4 3,800 5 3,700 a) Forecast the mileage for next year (6th year) using a 2-year moving average. b) Find the MAD based on the 2-year moving average. (Hint: You will have only 3 years of matched data.) c) Use a weighted 2-year moving average with weights of .4 and .6 to forecast next year?s mileage. (The weight of .6 is for the most recent year.) What MAD results from using this approach to forecasting? (Hint: You will have only 3 years of matched data.) d) Compute the forecast for year 6 using exponential smoothing, an initial forecast for year 1 of 3,000 miles, and a 5 .5. 4.25 The following gives the number of accidents that occurred on Florida State Highway 101 during the past 4 months: MONTH NUMBER OF ACCIDENTS January 30 February 40 March 60 April 90 Forecast the number of accidents that will occur in May, using least-squares regression to derive a trend equation. 4.27 George Kyparisis owns a company that manufactures sailboats. Actual demand for George?s sailboats during each of the past four seasons was as follows: YEAR SEASON 1 2 3 4 Winter 1,400 1,200 1,000 900 Spring 1,500 1,400 1,600 1,500 Summer 1,000 2,100 2,000 1,900 Fall 600 750 650 500 George has forecasted that annual demand for his sailboats in year 5 will equal 5,600 sailboats. Based on this data and the multiplicative seasonal model, what will the demand level be for George?s sailboats in the spring of year 5?

Paper#12731 | Written in 18-Jul-2015

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