Question 2 Part 1(a) York university parking services forecasted the number of parking passes issued monthly given the following table, if the Mean Error (ME) = 11, determine what the actual value of the number of parking passes issue must have been in May(A3). Month Number of Parking Passes issued Forecast March 1490 1455
Question 2 Part 1(a) York university parking services forecasted the number of parking passes issued monthly given the following table, if the Mean Error (ME) = 11, determine what the actual value of the number of parking passes issue must have been in May(A3). Month Number of Parking Passes issued Forecast March 1490 1455
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:Question 2
Part 1(a)
York university parking services forecasted the number of parking passes issued monthly given the
following table, if the Mean Error (ME) = 11, determine what the actual value of the number of parking
passes issue must have been in May(A3).
Month
Number of Parking Passes issued
Forecast
March
1490
1455
April
May
1040
1050
А3-?
2675
June
2525
2450
July
August
1900
1950
2122
2125
Part I(b)
York university parking services also wants to forecast the number of parking passes issued monthly and
revenue (in thousands) generated from these parking passes. The data for six months in 2021 is in the
table below.
Month
Number of Passes
Revenue(in thousands)
March
1490
170
April
May
1040
120
A3=?
300
June
2525
250
July
1900
270
August
2122
350
If you want to compare the forecast accuracy of these two different time series(number of passes issued
and revenue), what measurement of the forecast accuracy have you applied?
Part I(c)
Using the table given in Part I (b), Forecast the revenue of September using the 3-month moving average
method and the exponential smoothing method with a smoothing constant of 0.4.
Part I(d)
Using the forecast information of revenue in Part I(c), calculate the measurement of the forecast accuracy
you selected in Part I (b) Do you prefer the 3-month moving average method or the exponential
smoothing method? Why?
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