- 25 Marks
QMDM – APR 2024 – L2 – Q4 – Exponential Smoothing in Time Series Forecasting for Mango Demand
Using monthly demand data for mangos over 15 months, explain exponential smoothing, compute and compare forecasts using alpha=0.1 and 0.4 with initial forecast of 500, describe plots of actual vs forecasts, and comment on suitability.
Question
Kiki, the commercial mango seller has collected demand figures for mangos over the last 15 months in the table below:
| Month | Demand |
|---|---|
| 1 | 470 |
| 2 | 510 |
| 3 | 460 |
| 4 | 490 |
| 5 | 520 |
| 6 | 460 |
| 7 | 1500 |
| 8 | 1450 |
| 9 | 1550 |
| 10 | 1500 |
| 11 | 1480 |
| 12 | 1520 |
| 13 | 1500 |
| 14 | 1490 |
| 15 | 1500 |
(a) Explain briefly the term “Exponential Smoothing” in Time Series Analysis of the data above. [3 Marks]
(b) Use an initial forecast of 500 to compare Exponential Smoothing Forecasts with Smoothing Constant Values a = 0.1 and a=0.4.
(c) Plot the actual values of the time series and superimpose the forecast for the Smoothing Constant Values a= 0.1 and a=0.4 on the graph of the actual values.
(d) Comment on the suitability of the forecast from the Smoothing Constant Values a= 0.1 and a=0.4.
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QMDM – APR 2024 – L2 – Q4 – Exponential Smoothing in Time Series Forecasting for Mango Demand
Using monthly demand data for mangos over 15 months, explain exponential smoothing, compute and compare forecasts using alpha=0.1 and 0.4 with initial forecast of 500, describe plots of actual vs forecasts, and comment on suitability.
Kiki, the commercial mango seller has collected demand figures for mangos over the last 15 months in the table below:
(a) Explain briefly the term “Exponential Smoothing” in Time Series Analysis of the data above. [3 Marks]
(b) Use an initial forecast of 500 to compare Exponential Smoothing Forecasts with Smoothing Constant Values a = 0.1 and a=0.4.
(c) Plot the actual values of the time series and superimpose the forecast for the Smoothing Constant Values a= 0.1 and a=0.4 on the graph of the actual values.
(d) Comment on the suitability of the forecast from the Smoothing Constant Values a= 0.1 and a=0.4.
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