In: Statistics and Probability
The time series showing the sales of a particular product over
the past 12 months is contained in the Excel Online file below.
Construct a spreadsheet to answer the following
questions.
Use a=0.2 to compute the exponential smoothing forecasts for the time series (to 2 decimals).
Month |
Time-Series Value |
Forecast |
---|---|---|
1 | 105 | |
2 | 130 | |
3 | 125 | |
4 | 100 | |
5 | 90 | |
6 | 120 | |
7 | 150 | |
8 | 135 | |
9 | 95 | |
10 | 75 | |
11 | 100 | |
12 | 105 | |
13 |
Use a smoothing constant of a=0.5 to compute the exponential smoothing forecasts (to 2 decimals).
Month |
Time-Series Value |
Forecast |
---|---|---|
1 | 105 | |
2 | 130 | |
3 | 125 | |
4 | 100 | |
5 | 90 | |
6 | 120 | |
7 | 150 | |
8 | 135 | |
9 | 95 | |
10 | 75 | |
11 | 100 | |
12 | 105 | |
13 |
Compute MSE (to 2 decimals).
MSE ( a= 0.2 ) : (___)Month | Time-Series Value |
1 | 105 |
2 | 130 |
3 | 125 |
4 | 100 |
5 | 90 |
6 | 120 |
7 | 150 |
8 | 135 |
9 | 95 |
10 | 75 |
11 | 100 |
12 | 105 |
13 |
Formula for exponential smoothing forecast
where
is the forecast demand for the time t
is the smoothing constant
is the actual value for time t-1
is called the damping factor
is the forecast value for the time t-1
We will now put the formula in Excel.
Formula for MSE (Mean Square Error)
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