- Create a line chart and identify the time series components in the time series. Then, compute the
correlation between the time series variable and time using either the =CORREL() function or the correlation tool in the date analysis tool pack. Justify your answer. (Hint: it should be some combination of
average or base, cycle, trend, and random variation.) - Create as many forecasts as possible on the historical data using each of the methods below.
a. 3-period moving average.
c. Exponential smoothing forecast with alpha = 0.8.
d. Trend forecast (whether or not there is a trend). Use the =TREND() function in Excel.
IMPORTANT NOTES: When computing your moving average forecasts, do not use the Moving Average
Data Analysis tool. This tool will not give you a valid forecast because it uses the current period in the computation. Instead, use the AVERAGE() function. Also, for both the ES and the MA forecasts, do not include the period you are forecasting in the history you are using to compute the forecast. - Starting with the fourth period, compute the MAE for each forecasting model, and choose the best model
based on this analysis. - Using the best model, make a new forecast for the next period.
Deliverables
Please place all of your analysis on a single spreadsheet. Clearly label your answers. When you have completed the assignment, post your Excel file on the HW 4 assignment dropbox.
Hints: In this assignment, you are using your entire history to build good models and to test the forecasting skill of the models. Once you have computed the forecasts and calculated the MAEs for each model, you will choose the most accurate model on historical data to make a future forecast. The moving average
forecasts will begin at period 4, the ES forecasts will begin at period 2 (with the naïve starting value), and
the trend forecasts will begin in period 1.
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