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# Passenger Movement Forecast At Delhi International Airport

1015 words - 5 pages

Term paper
Forecasting of Aircraft Movements: Delhi Airport.
Submitted T*o* Submitted By
Objective
The objective of the study is to develop an econometric model by which Delhi airport operator can forecast the number of aircraft movement in a particular month of the year, given a certain number of passenger and tones of freight. By knowing the number of aircraft movement an airport operator can take decision for potential requirements such as number and size of runway required, whether a new terminal building is required or not, number of taxiways, bays, gates, etc. it will also help operator in its strategic planning and organizational planning.
Methodology
To develop the ...view middle of the document...

4%
Analysis of Variance
Source DF SS MS F P
Regression 2 190397447 95198724 366.24 0.000
Residual Error 33 8577907 259937
Total 35 198975355
Source DF Seq SS
No. of Pax 1 188290737
Freights in Tonne 1 2106710
Interpretations:
R square is 95.7% which means95.7% variation in Number of Aircraft movement can be explained or depend on the number of passenger movement and freight movements.
For both independent variables are significant as T stat value for paxvariable is 20.83 and freight is 2.85
Test of Multicollinearity
As R square value is 95.7%, there may be multicollinearity exists,
*Correlations: No. of Pax*, Freights in Tonne Pearson correlation of No. of Pax and Freights in Tonne = 0.554
P-Value = 0.000
VIF= (1/1-Ri)
= 2.22 which means low level of multicollinearity.
SE of coefficients: Predictor SE Coef T P
Constant 1067 -0.05 0.960
No. of Pax 0.0003381 20.83 0.000
Freights in Tonne 0.03783 2.85 0.008
As standard error of constant is high and the t stat is not significant which indicates the existence of multicollinearity. Other variable such as No. of passenger and freight are low, and t value shows both variables are significant.
Dropping of some observation:
*Regression Analysis: Aircraft mov*. Versus No. of *Pax*, Freights in
The regression equation is
Aircraft movement = - 596 + 0.00708 No. of Pax + 0.123 Freights in Tonne
Predictor Coef SE Coef T P
Constant -596 1192 -0.50 0.621
No. of Pax 0.0070757 0.0003628 19.50 0.000
Freights in Tonne 0.12293 0.04078 3.01 0.005
S = 520.039 R-Sq = 95.1% R-Sq(adj) = 94.7%
Analysis of Variance
Source DF SS MS F P
Regression 2 156670478 78335239 289.66 0.000
Residual Error 30 8113225 270441
Total 32 164783703
Theils measure
Excluding freight movement:
The regression equation is
Aircraft movement = 2630 + 0.00760 No. of Pax
S = 583.946 R-Sq = 93.6% R-Sq(adj) = 93.4%
Analysis of Variance
Source DF SS MS F P
Regression 1 154212905...

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