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Analysis of Three Universities

In:

Submitted By bilaljanjua
Words 4884
Pages 20
BUSINESS STATISTICS

10123046 SalmanRiaz

MBA (3.5 years)
FALL 2010

SUBMITTED TO: Mr. ABID AWAN
SUBMISSION DATE: February 25, 2015

Correlation analysis of Three Universities
Correlation analysis of GIFT University

Tables 1 | ECA (X1) | HOURS (X2) | COURSE(X3) | Degree(X4) | CGPA(Y) | ECA (X1) | 1 | | | | | HOURS (X2) | 0.020546566 | 1 | | | | COURSE(X3) | 0.110931612 | -0.003577178 | 1 | | | Degree(X4) | 0.055096599 | -0.163985608 | -0.09382865 | 1 | | CGPA Y (Y) | 0.14111477 | 0.111037212 | 0.230369489 | 0.220496482 | 1 |

Explanation: From the above calculated table value, we can see that the relation between independent variable X1, X2, X3, X4 and an dependent variable Y. X1 (ECA) and X2 (hours) shows that there is a 2.05% correlation between them which is a strong positive correlation. X1 (ECA) and X3 (course) shows that there is a 11.09% correlation between them which is a strong positive correlation. X1 (ECA) and X4 (marks) shows that there is a 5.50% correlation between them which is a strong positive correlation. X1 (ECA) and Y (CGPA) shows that there is a 14.41% correlation between them which is a strong positive correlation which indicate that our dependent variable CGPA depend on ECA also. X2 (IQ hours) and X3 (hours) shows there is a -0.35% correlation between them which is a negative correlation. X2 (IQ hours) and X4 (marks) shows -16.39% correlation between them which is a negative correlation. X2 (IQ hours) and Y (marks) shows 11.10% correlation between them which is a positive correlation which indicate that our dependent variable CGPA depends on times spend on study also. X3 (quantitative subject studied) and X4 (degree) shows -9.38% correlation between them which is a negative correlation. X3 (quantitative subject studied) and Y (CGPA) shows 23.03% correlation between them which is a

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