Instruction: 1) Answer must be type-written nicely in Microsoft Word (Font size 12, Times New Roman). Kindly use also functions; insert > equation/symbol for purpose of writing your report. 2) The report should include a cover page as shown in Appendix I. The coursework must be entirely your own group work. 3) The assignment should be submitted in soft copy. 4) The due date is on WEEK 12 (Sunday, 11/04/2021) before 5pm. A penalty of 5 marks deduction of the maximum mark applicable to the assessment will be levied for each day of late submission. Weekends and Public Holidays are counted as one (1) day late. Submission can be done via a link that will be provided in WBLE. Kindly save your le in word document as: Assignment 2_[Tutorial Group No.#]_[Group Leader Name]. Problem: Solving The dean from one of our local university wants to raise the admission standards of Masters of Accounting and Finance (MAF) program due to overwhelming applications for the past several intakes, while she also concerned about the quality of graduates. She understood that the current admission policy requires the applicants to have completed at least 3 years of working experience and having their undergraduate degree with a B-average or better. However, because the program had recently converted from 2-year program to a 1-year program, the number of applicants has increased substantially. She plans to develop a method that can predict an applicant's performance in the program. She believes that student's success in the program (MAFGPA) can be predicted by Undergraduate Grade Point Average (UGPA), Graduate Admission Test (GAT) and number of years of work experience (Work). A randomly selected sample of students who completed the MAF was selected. You are required to assist the dean to administer and develop a plan to decide which applicant to admit. Support your nding in model diagnostic and model assessment. You may use the given output in assessing the development of the method. Page 1 of 2 7:017 Done Assignment2_instruction and... SUMMARY OUTPUT Regression Statistics Multiple R 0.6808 R Square 0.4635 Adjusted R 0.4446 Standard Error 0.788 Observation 89 ANOVA df SS MS F Significance F Regression 3 45.60 15.20 24.48 0.0000 Residual 85 52.77 0.62 Total 88 98.37 Coefficients Standard Error t Stat P-value Intercept .466 1.506 0.31 0.7576 UGPA 0.063 0.120 0.52 0.6017 GAT 0.011 0.001 8.16 0.0000 Work 0.093 0.031 3.00 0.0036 Standardized residuals 40 30 20 10 -2.5 -1.5 -0.5 0.5 1.5 2.5 More Figure 1 Residuals 19 Figure 2 (25 marks) [Total: 25 marks] Page 2 of 2
