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?