Each question needs to be completed on seperate pages in excel.

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.

4.3

Year- 1  2  3  4  5  6  7  8  9  10  11

Demand-7  9  5  9  13  8  12  13  11  7

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 is first number, mileage is second)

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.