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.

1. Forecasting Trend
Time series Model
Assignment
Name: Rania Hassan Ali
MBA : Group ( A )

2. Performance objectives:
1. The participant should be able
to develop a series of times model
to predict male students.

3. 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.

4. Table 1

5. Objectives of modelling :
1) Expect the number of students
during the study period
2) To detect the different ratios of
male students' entrance to different
exam dates

6. Methods:
1. This is a documentary study using time series
data covering the period 2016 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.

7. Results:
Trend line :
Ŷ = a+ bx
b= Ʃxy – nx ȳ
Ʃx2 - nx2

8. b = slope of the regression line
g = summation sign
x = known values of the
independent variable
y = known values of the dependent
variable
x = average of the x -values
y = average of the y -values
n = number of data points or
observations
‫ب‬
=
‫االنحدار‬ ‫خط‬ ‫ميل‬
g =
‫الجمع‬ ‫عالمة‬
‫س‬
=
‫المستقل‬ ‫للمتغير‬ ‫المعروفة‬ ‫القيم‬
y =
‫التابع‬ ‫للمتغير‬ ‫المعروفة‬ ‫القيم‬
‫س‬
=
‫س‬ ‫القيم‬ ‫متوسط‬
y =
‫القيم‬ ‫متوسط‬
y
‫ن‬
=
‫المالحظات‬ ‫أو‬ ‫البيانات‬ ‫نقاط‬ ‫عدد‬

10. Evaluating the model: