The following time series shows the sales of a particular product over the past

Question

The following time series shows the sales of a particular product over the past 12 months. can be found in the below excel file.

https://drive.google.com/file/d/1gIpr0IBYUGgCIRSO7g3mqZ84F89vJU_P/view?usp=sharing

1. Using the three-month moving average, what is the Mean Squared Error (MSE)?

(Round your answer to 2 decimal places. Negative values should be indicated by a minus sign.)

2.  Using the three-month moving average, what is the forecast for month 13 ?

(Round your answer to 2 decimal places. Negative values should be indicated by a minus sign.)

3. Using the exponential smoothing approach for ? .3 or .7, what is the Mean Squared Error (MSE)?  

(Round your answer to 2 decimal places. Negative values should be indicated by a minus sign.)

4. Using the exponential smoothing approach for , .3 or .7, what is the forecast for month 13?

(Round your answer to 2 decimal places. Negative values should be indicated by a minus sign.)

5. Using the exponential smoothing approach for , .5 or .5, what is the Mean Squared Error (MSE)?

(Round your answer to 2 decimal places. Negative values should be indicated by a minus sign.)

6. Using the exponential smoothing approach for , .5 or .5, what is the forecast for month 13?

(Round your answer to 2 decimal places. Negative values should be indicated by a minus sign.)

7. Does a smoother constant of .3 or .5 provide more accurate forecasts based on MSE ?

.3 .5

Explanation / Answer

SOLUTION: From the given information, we get

1) Mean Squared Error can be found from following table:

Shipments on Time

Root Mean Squared Error (RMSE)

2)Forecast for month 13:

3) Exponential Smoothening with alpha=0.3 in below table

4) Using alpha=0.3 forecast for 13th month

5) With alpha=0.5 Mean Squared Error(MSE) is:

6) Forecast for month 13:

7) When alpha=0.3,RMSE is:15.14

When alpha=0.5,RMSE is:11.13

Since RMSE is less for alpha=0.5 , so alpha=0.5 gives better results.Hence alpha=0.5 gives accurate results

Week Shipments on Time 1 105 2 135 3 120 4 105 5 90 6 120 7 145 8 140 9 100 10 80 11 100 12 110

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