Quarter Year 1 Year 2 Year 3 Year 4 Year 5 1 20 37 75 92...

Quarter	Year 1	Year 2	Year 3	Year 4	Year 5
1	20	37	75	92	176
2	100	136	155	202	282
3	175	245	326	384	445
4	13	26	48	82	181

Question 3

Again ignore any trend or seasonality in the data. Suppose the company uses exponential smoothing to make forecasts.

What are the forecasts for periods Q2 Year 1 through Q4 Year 5 assuming alpha = 0.3. Assume that the forecast for Q1 Year 1 was 25 units.
What are the forecasts for periods Q2 Year 1 through Q4 Year 5 assuming alpha = 0.8. Assume that the forecast for Q2 Year 1 was 25 units.
Compare the accuracies of the forecasts in (a) and (b) using Mean Absolute Percent Error. Which value of alpha gives us the better forecasts?

Question 4

Now make adjustments for trend and seasonality.

Quantify the trend in the time series. What does the trend equation tell you?
Quantify the seasonality in the time series by calculating seasonality indexes. What do these indexes tell you?
Using the trend and the seasonality information from (a) and (b) make forecasts from Q1 Year 1 through Q4 Year 5.
Use MAPE to calculate the accuracy of your forecasts.

Question 5

Compare the preferred method in Question 2, the preferred method in Question 3, and the method in Question 4. Which one would you choose on the basis of MAPE?
Using the method in Question 4 make forecasts for the 4 quarters of Year 6.

Solutions

Expert Solution

please post the other questions separately.

thanks

ekkarill92 answered 1 year ago

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