The following monthly sales of chocolate boxes (in thousands of AUS dollars) have been recorded for January, February, March, and April, respectively: 9.5, 8, 9, 9. Examining the forecasting accuracy for the month of April only: Explain which of the following forecasting method would you recommend: (i) the Naïve method, (ii) the Average method, or (iii) the Simple exponential smoothing method (assuming alpha= 0.8 and initial state (in December) of 8.5)

The following monthly sales of chocolate boxes (in thousands of AUS dollars) have been recorded for January, February, March, and April, respectively: 9.5, 8, 9, 9. Examining the forecasting accuracy for the month of April only: Explain which of the following forecasting method would you recommend: (i) the Naïve method, (ii) the Average method, or (iii) the Simple exponential smoothing method (assuming alpha= 0.8 and initial state (in December) of 8.5)

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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The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.
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The file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?
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An electronic appliance manufacturer wants to know if there is a relationship between percentage change in deposable personal income which is reported quarterly by the government, and the percentage change in appliances sold by the manufacturer following same years of quarterly data. Brenda Chee and Clarence Paulus lead an analyst team has obtained data for the past 10 quarters. (Hint: Provides your answers in two decimal points) (a) What forecasting model should be used for this data. Why? (b) Develop the forecasting model that you have proposed in (a). (c) Compute the relationship for these data. In your opinion, is the relationship between independent variable strong enough to base a predictive the dependent variable? Explain your answer.