Compute the mean absolute deviation and mean square error, Basic Statistics

Toyota Motors introduced a hybrid car Hybrid G in the U.S. market in 2006. In the first three years, the sales of Hybrid G were strong due to the buzz surrounding the hybrid car concept and also lack of competition. Sales of Toyota's Hybrid G started declining in 2009 following the introduction of a new hybrid model by Honda. Toyota is in critical need of a better forecasting method. They need your help to evaluate alternative forecasting methods and provide suggestions. The following table contains the past 12 months' sales data (Note: Month 1 refers to sales made 12 months ago, month 12 refers to sales made last month.)

a. Use a 3-month simple moving average to forecast sales for months 4 to 13. Compute the Mean Absolute Deviation (MAD) and the Mean Square Error (MSE) of the forecasts for months 4 to 12.

b. Using a 3-month weighted average method with weights of 0.5, 0.3 and 0.2 (most recent, next most recent, and third most recent month, respectively) for months 4 to 13. Again, compute the MAD and MSE of the forecasts for months 4 to 12 with the weighted moving average method.

c. Using exponential smoothing method, compute two sets of forecasts for the sales of Hybrid G for months 2 to 13, corresponding to α values of 0.2 and 0.5. Assume that the forecast for month 1 is 1376.

d. Continue part c. Compute the MAD and Mean Absolute Percentage Error (MAPE) using the forecast errors from months 2-12 for each of these two sets of forecasts. Which α value produces a more accurate forecast?

e. Use the trend-adjusted exponential smoothing method to forecast sales for months 2 to 13, assuming S1=1376 and T1=-25 and set α=0.8 and β=0.2.

f. Develop a simple linear regression model using month as the independent variable to forecast the sales of Hybrid G for month 13.

Posted Date: 3/6/2013 4:38:53 AM | Location : United States







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