Probability Concepts

timer Asked: Mar 1st, 2016

Question description

1. What is a time-series forecasting model?

2. What is the difference between a causal model and a time-series 


3. What are some of the problems and drawbacks of the moving 

average forecasting model?

4.What effect does the value of the smoothing constant have on the 

weight given to the past forecast and the past observed value?

5.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:


1 450 

2 495 

3 518 

4 563

5 584

6 ? 

 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.

5-22 Using smoothing constants of 0.6 and 0.9, develop 

forecasts for the sales of Cool-Man air conditioners (see Problem 


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 


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