S York University is looking for ways to increase enrollment. The Registrar's Office conducts the orientations...

 

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S York University is looking for ways to increase enrollment. The Registrar's Office conducts the orientations for future students at the beginning of the month. As part of the planning, they scrutinize the number of prospective students that attended the orientation and will be enrolled in York. They have collected data for the number of orientations conducted and the number of students enrolled (in thousands) from January to June, as mentioned below. Jan Feb Mar Apr May June Number of orientations Number of students conducted enrolled 85 96 88 90 Vaar Parta) Forecast the number of students enrolled for the month of July using the 2-period weighted moving average method, using a weight of three quarters for the most recent observation, and one quarter for the second most recent. Also, forecast the number of students enrolled for the month of June using the exponential smoothing method with a smoothing constant of 0.2. 4.6 Part b) The Registrar's Office wants to compare the forecast accuracy of these two-time series. Which measure of accuracy would they apply? amor 6.0 5.5 Part c) Using the previous forecast information of the number of students enrolled in Part a), calculate the forecast accuracy that the Registrar's Office selected in Part b). Which method would they prefer? The 2-period weighted moving average method or the exponential smoothing method and why? Part d) Using the exponential smoothing method with a smoothing constant of 0.8, an analyst from the Registrar's Office also forecasts the number of students enrolled and calculated MAPE = 10.9667 Which smoothing constant would he prefer, 0.8 or 0.2, and why? To Part e) the Quarterly number of orientations conducted for the periods of 2020-2022 is shown below. iTmllim Na La petersili! Year Fall Winter Summer 2020 265 2021 2022 370 400 380 506 402 The Registrar's Office analyzed this data by applying the regression tool and produced the following forecast modell Forecast 160.6667 + 91.4444 Fall + 60.7222 Winter + 9.0556 / The variables in the equation above have been introduced: Fall 1 if it is Fall, 0 otherwise, Winter - 1 if it is Winter, O otherwise; and t = time period. Forecast the number of orientations conducted in Fall, in the year 2024. S York University is looking for ways to increase enrollment. The Registrar's Office conducts the orientations for future students at the beginning of the month. As part of the planning, they scrutinize the number of prospective students that attended the orientation and will be enrolled in York. They have collected data for the number of orientations conducted and the number of students enrolled (in thousands) from January to June, as mentioned below. Jan Feb Mar Apr May June Number of orientations Number of students conducted enrolled 85 96 88 90 Vaar Parta) Forecast the number of students enrolled for the month of July using the 2-period weighted moving average method, using a weight of three quarters for the most recent observation, and one quarter for the second most recent. Also, forecast the number of students enrolled for the month of June using the exponential smoothing method with a smoothing constant of 0.2. 4.6 Part b) The Registrar's Office wants to compare the forecast accuracy of these two-time series. Which measure of accuracy would they apply? amor 6.0 5.5 Part c) Using the previous forecast information of the number of students enrolled in Part a), calculate the forecast accuracy that the Registrar's Office selected in Part b). Which method would they prefer? The 2-period weighted moving average method or the exponential smoothing method and why? Part d) Using the exponential smoothing method with a smoothing constant of 0.8, an analyst from the Registrar's Office also forecasts the number of students enrolled and calculated MAPE = 10.9667 Which smoothing constant would he prefer, 0.8 or 0.2, and why? To Part e) the Quarterly number of orientations conducted for the periods of 2020-2022 is shown below. iTmllim Na La petersili! Year Fall Winter Summer 2020 265 2021 2022 370 400 380 506 402 The Registrar's Office analyzed this data by applying the regression tool and produced the following forecast modell Forecast 160.6667 + 91.4444 Fall + 60.7222 Winter + 9.0556 / The variables in the equation above have been introduced: Fall 1 if it is Fall, 0 otherwise, Winter - 1 if it is Winter, O otherwise; and t = time period. Forecast the number of orientations conducted in Fall, in the year 2024.