Question

The dean of Mihaylo Business School is forecasting total student enrollment for next year based on the following historical data: Year Total Enrollment 2015 1600 2016 2000 2017 2200 2018 2600 2019 3000 What is 2020's forecast using a 2-period moving average? Select one: a. 2,800 b. None of the choices c. 3,000 d. 1,960 e. 2,450 What is the MAPE value based on 2 year moving average? Select one: a. None of the choice b. 0.191 c. 0.178 d. 0.144 e. 0.237 What is the forecasted value of 2020 by using a 3 year weighted moving average by using weights of 0.6, 0.3 and 0.1. Select one: a. 2480 b. 2800 c. 2680 d. None of the choices e. 2400 a. None of the choice b. 0.191 c. 0.178 d. 0.144 e. 0.237 What is the MSE value based on exponential smoothing forecast with smoothing constant of 0.4? Select one: a. 1,557,436 b. None of the choices c. 576 d. 1,297,863 e. 357,985 Compare 2 year moving average and exponential smoothing with alpha=0.4, which forecasting approach is better? Using MAE as your forecast accuracy measure. Select one: a. Exponential smoothing with alpha=0.4 b. 2 year moving average

Answer 1

a) 2 period moving average for year 2020

year	enrollment	2 period moving average	differece	mean absolute percentage error
2015	1600
2016	2000
2017	2200	1800	400	18.18
2018	2600	2100	500	19.23
2019	3000	2400	600	20.00
2020		2800
mean absolute percentage error				19.14%

1) a) 2800 (as shown in table)

2) b) MAPE is 0.191

3) weighted moving average

=

year	enrollment	three month weighted moving average
2015	1600
2016	2000
2017	2200
2018	2600	2080
2019	3000	2420
2020		2800

forecast for 2020 is 2800 using weghted moving average method

4) for exponential smoothing let we take the forecast data of 2 period moving average

given

year	enrollment(Dt-1)	2 period moving average(Ft-1)	Forecast error	multiply by 0.4	new forecast
2015	1600
2016	2000
2017	2200	1800	400	160	1960
2018	2600	2100	500	200	2300
2019	3000	2400	600	240	2640
2020	2280	2800	-520	-208	2592
		Assuming old forecast as average of enrolment from 2015 to 2019 we get
		1600+2000+2200+2600+3000/5	2280