1. ECONOMETRIC
“FORECASTING”
BY
DR. ILHAM SENTOSA
dr.ilhamsentosa@limkokwing.edu.my

2. Exercise Data 3 - Business Analysis

3. Perform Business Analysis
• Data on the average of customer’s income
in radius 3 km from restaurant (I);
• Number of competitor in radius 3 km (N);
• Number of population in radius 3 km from
restaurant (P);
• Number of customer per year (Y).

4. Case Study
• I = Income – 3 km from restaurant
• N= Competitor in 2 km
• P = Population in 3 km from restaurant
• Y = No of Customer

5. Data of Income, Competitor, Population and Customers
Obs. I N P Y
1 13,240 3 65,044 107,919
2 22,554 5 101,367 118,866
3 16,916 7 124,989 98,579
4 20,967 2 55,249 122,015
5 19,576 3 73,775 152,827
6 15,039 5 48,484 91,259
7 21,857 8 138,809 123,550
8 26,435 2 50,244 160,931
9 24,024 6 104,300 98,496
10 14,987 2 37,852 108,052

6. Instructions
1. Data Key In
2. Perform Multiple Regression Analysis
3. Analyze: Model Summary Table and
Coefficient table

7. SPSS Output : Adj R 2
Model Summary
Change Statis tics
Adjus ted Std. Error of R Square
Model R R Square R Square the Es tim ate Change F Change df1 df2 Sig. F Change
1 .791a .626 .438 17.263183 .626 3.342 3 6 .097
a. Predictors: (Cons tant), P, I, N

8. PREDICTION USING REGRESSION COEFFICIENTS
a
Coefficients
Uns tandardized Standardized
Coefficients Coefficients Correlations Collinearity Statis tics
Model B Std. Error Beta t Sig. Zero-order Partial Part Tolerance VIF
1 (Cons tant) 82.167 28.171 2.917 .027
I 2.518 1.472 .477 1.711 .138 .564 .573 .427 .801 1.248
N -11.008 6.184 -1.058 -1.780 .125 -.437 -.588 -.445 .177 5.658
P .427 .405 .650 1.055 .332 -.163 .396 .264 .165 6.075
a. Dependent Variable: Y

9. Multiple Regressions Equation
Y = 82.167 – 11.008(N) + 0.427(P) + 2.518(I)

10. Y = 82.167 – 11.008(N) + 0.427(P) + 2.518(I)
• Analysis:
1. 1 New Restaurant (N) in 3 km, Customer reduce
to 11.008 person.
2. Population in 3km increase to 1000 people,
customer increase to 427 person. (Population
Increase for 1 person , Customer increase to
0.427 person).
3. Customer Income in 3km Increase for RM.100
per year, Customer to serve also increase for 251
person per year. (Income increase for RM.1,
Customer to serve in crease for 2.5 people).
4. Adjusted R2 = 43.8% , high influence

11. What is Your
Decision?

12. Thank You