1. 1 Preparation for Final Exam How to answer question related to computer output?

2. 2 Multiple Regression Ahmad a manager at a university feels that lecturers ought to have high intentions to share information among them so that the competitiveness of the university can be enhanced. Lately there have been many complaints about the poor quality of students from the public institutions of higher learning. Ahmad has collected data from 96 lecturers and the variables that has been emphasized are Gender (gender of the respondent 1 = Male, 0 = Female), Reciprocal (Reciprocal relationship between lecturers), Self (self efficacy), Climate (Climate of the organization) and Intention (Intention to share information). The data was analysed using SPSS and the output is given below:

3. 3 Data IDReciprocalSelfClimateGender Intention 13.604.004.3313.60 2 4.003.5003.20 32.804.003.0014.00.................. 942.00 2.1715.00 953.805.002.6704.60 963.805.003.5014.00

4. 4 Model Summary Model Summary(b) ModelR R Square Adjusted R Square Std. Error of the Estimate Durbin- Watson 1.787(a).619.603.403761.633 a Predictors: (Constant), climate, self, gender, reciprocal b Dependent Variable: intention

5. 5 Test for the Model

6. 6 Test for Individual Variables

7. 7 Assumptions (Multicollinearity)

8. 8 Data Normally Distributed

9. 9 Errors Normally Distributed

10. 10 Outliers Casewise Diagnostics(a) 1.432143.28138.803.385 56 1.517553.48248.004.105 45 Residual Predicted ValueIntention Std. ResidualCase Number a Dependent Variable: Intention

11. 11 Constant Variance (Homosdedasticity)

12. 12 Linearity

13. 13 Linearity

14. 14 Linearity

15. 15 Multiple Regression The MBA was started in USM since 1995 and the dean would like to analyze the factors that influence the performance of the candidates. One hundred students who have graduated the last three years were selected and their GPA during their first degree, GMAT score and their number of years working experience before they joined were recorded. The data was analyzed using the SPSS software and the output is presented below:

16. 16 Data MBAGPAUNDERGPAGMATWORK 8.4310.895849 6.5810.384837 8.1510.394844............ 8.2711.026364 7.5710.725154 8.510.226364

17. 17 Model Summary

18. 18 Test for the Model

19. 19 Test for Individual Variables

20. 20 Assumptions

21. 21 Data Normally Distributed

22. 22 Errors Normally Distributed

23. 23 Outliers Casewise Diagnostics(a) 1.432143.28138.803.385 56 1.517553.48248.004.105 45 Residual Predicted Value GPA Kursus MBA Std. ResidualCase Number a Dependent Variable: GPA Kursus MBA

24. 24 Constant Variance (Homosdedasticity) GPA Kursus MBA

25. 25 Linearity GPA Kursus MBA GMAT GPAMBAGPAMBA