Linear regression forecast-exponential smoothing forecast

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Reference no: EM131036818

The don’t drink and drive mountain bike deal in the spokane area wants to be able to forecast accurately the demand for the don’t drink and drive 2120VT bike. From sales records the dealer has accumulated the following data for the past five years. 2011=3400 sales 2012=4000 sales 2013=5000 sales 2014=6800 sales 2015=5100 sales A. Using linear regression, the slope of this time series of data is 620 and the intercept is 3000. Based on linear regression, what would the forecasts be for 2011-2015? B. Develop exponential smoothing forecasts for 2013, 14, and 2015 with a smoothing constant of .22. To initialize the process you may assume that the forecast for 2011 was 2800. C. Calculate the MAD covering 2013-2015 for linear regression forecast and exponential smoothing forecast. Which forecasting method appears to be better for the dealers data? Why?

Reference no: EM131036818

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