5-2 What is a time-series forecasting model?
5-3 What is the difference between a causal model and a time-series
model?
5-5 What are some of the problems and drawbacks of the moving
average forecasting model?
5-6 What effect does the value of the smoothing constant have on the
weight given to the past forecast and the past observed value?
5-8 What is MAD, and why is it important in the selection and use of
forecasting models?
5-21 Sales of Cool-Man air conditioners have grown
during the past 5 years:
YEAR SALES
2. The sales manager had predicted, before the business started,
that year 1’s sales would be 410 air conditioners. Using
exponential smoothing with a weight of α = 0.30, develop
forecasts for years 2 through 6.
3. 5-22 Using smoothing constants of 0.6 and 0.9, develop
forecasts for the sales of Cool-Man air conditioners (see Problem
5-21).
4. 5-23 What effect did the smoothing constant have on the
forecast for Cool-Man air conditioners? (See Problems 5-21 and
5-22.) Which smoothing constant gives the most accurate
forecast?
5. 5-24 Use a three-year moving average forecasting model to
forecast the sales of Cool-Man air conditioners (see Problem 5-
21).
6. 5-25 Using the trend projection method, develop a forecasting
model for the sales of Cool-Man air conditioners (see Problem 5-
21).
7. 5-26 Would you use exponential smoothing with a smoothing
constant of 0.3, a 3-year moving average, or a trend to predict the
sales of Cool-Man air conditioners? Refer to Problems 5-21, 5-24,
and 5-25.
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