1. Plot the data on a two-year time horizon from 2005 through 2006. Connect the data points to make a time series plot.
2. Develop a trend-line equation using linear regression and plot the results.
3. Estimate the seasonal adjustment factors for each month by dividing the average demand for corresponding months by the average of the corresponding trend-line forecasts. Plot the fitted values and forecasts for 2007 given by Trend x Seasonal.
4. Smooth the time series using Holt's linear exponential smoothing with three sets of smoothing constants: (α = .1, β = .1), (α = .25, β = .25), and (α = .5, β = .5). Plot the three sets of smoothed values on the time series graph. Generate forecasts through the end of the third year for each of the trend-adjusted exponential smoothing possibilities considered.
5. Calculate the MAD values for the two models that visually appear to give the best fits (the most accurate one-step-ahead forecasts).
6. If you had to limit your choice to one of the models in Questions 2 and 4, identify the model you would use for your business planning in 2007, and discuss why you selected that model over the others.
The Small Engine Doctor is the name of a business developed by Thomas Brown, who is a mail carrier for the U.S. Postal Service. He had been a tinkerer since childhood, always taking discarded household gadgets apart in order to understand "what made them tick." As Tom grew up and became a typical suburbanite, he acquired numerous items of lawn and garden equipment.