Th e manager of a small health clinic needs to forecastdemand for laboratory services in the facility. Data from the lastsix weeks are available and are, respectively, 330, 350, 320, 370, 368,and 343 tests. Th e manager decides to use a forecasting techniqueknown as the three-period moving average. For this technique,the most recent three weeks’ demands are averaged together toproduce the forecast for the upcoming week. For example, weeks1–3 are used to produce the forecast for week 4.(a) Construct a spreadsheet model to help the managerforecast demand. Assume that this technique has beenin place in the previous weeks as well, and generate theforecasted demand for week 7. You will not be able togenerate forecasted demands for weeks 1–3.(b) Expand the model to calculate the error in the forecasteach week. Th e error should be calculated as the actualdemand for the week minus the forecasted demand.Which week had the largest error? Which had the smallesterror? What does it mean that some errors are positiveand some are negative?

Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter13: Regression And Forecasting Models
Section13.3: Simple Regression Models
Problem 2P: The file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a...
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Th e manager of a small health clinic needs to forecast
demand for laboratory services in the facility. Data from the last
six weeks are available and are, respectively, 330, 350, 320, 370, 368,
and 343 tests. Th e manager decides to use a forecasting technique
known as the three-period moving average. For this technique,
the most recent three weeks’ demands are averaged together to
produce the forecast for the upcoming week. For example, weeks
1–3 are used to produce the forecast for week 4.
(a) Construct a spreadsheet model to help the manager
forecast demand. Assume that this technique has been
in place in the previous weeks as well, and generate the
forecasted demand for week 7. You will not be able to
generate forecasted demands for weeks 1–3.
(b) Expand the model to calculate the error in the forecast
each week. Th e error should be calculated as the actual
demand for the week minus the forecasted demand.
Which week had the largest error? Which had the smallest
error? What does it mean that some errors are positive
and some are negative?

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