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Forecasting Trend
Time series Model
Assignment
Dr. Magdy Abd Elfatah
Name: Rania Hassan Ali
MBA : Group ( A )
Performance objectives:
1. The participant should be able
to develop a series of times model
to predict male students.
Case study:
Table 1 shows the number of male students
enrolled at the Faculty of Commerce, Cairo
University between 2016 and 2019
a) calculate the trend line .
b monthly seasonal indices are computed.
c Estimating the number of males expected in
the academic year 2019/2020.
d. Discuss the model.
Objectives of modelling :
Predict the number of students
over the next year
Methods:
1. This is a documentary study using time series
data covering the period 2015 to 2019.
2. The dependent variable was the number of male
students registered in the exam.
3. For the starting point, we showed a simple
bivariate regression model using an independent
variable time factor.
Table 1
Number Of
Male Students
Year
Academic Year
5269
1
2015/2016
5366
2
2016/2017
4552
3
2017/2018
6294
4
2018/2019
10501
5
1019/2020
xy
2
x
Number Of
Male Students
Year
5269
1
5269
1
10732
4
5366
2
13656
9
4552
3
25176
16
6294
4
54833
=
Ʃxy
2
30
=
Ʃx
Ʃy = 21481
Ʃx = 4
Table 2
Trend line :
ẍ = Ʃx = 4 / 4 = 1
n
ȳ = Ʃy = 21481 / 4 = 5370.25
n
b= Ʃxy – n ẍ ȳ = 54833 – 4(1) (5370.25) = 1282.8
Ʃx2 - n ẍ2 30 – 4 (1)
a= ȳ - bẍ = 5370.25 – 1282.8 = 4087.45
Ŷ = a+ bx = 4087.45 + 1282.8 x
(
Number Of Male Students on ( 2019/2020
Ŷ = 4087.45 + 1282.8 (5( = 10501
0
2000
4000
6000
8000
10000
12000
1 2 3 4 5
Increase the expected number of
male students applying to the
Faculty of Commerce from 6294 for
the year 1019 to 10501 in the next
year 2020

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ass. 1 om.ppt