You can use excel. X University has contacted us in an effort to better understa

Question

You can use excel.

X University has contacted us in an effort to better understand the outcome of business students seeking a Bachelor of Business degree in Australia. In particular, they wish to seek what is a larger driver of student outcomes, student satisfaction with their program or the prerequisites of students arriving at the university. We have collected information on the average salary of business graduates from 39 universities across Australia.  

a. Run a multiple linear regression using the data and show the output from Excel. Exclude the dummy variable “OTHER” from the regression results. (1 Mark)

b. Is the overall model statistically significant at the 5% level of significance? Use the p-value approach. (1/2 Mark)

c. Based on the results of the regressions, what other factors would have influenced graduate salary? Provide a couple possible examples and indicate their predicted relationship with graduate salary if they were included. (1 Mark)

e. Predict the average graduate salary of a student enrolled in a ATN in Victoria that has an ATAR requirement of 80 and a student satisfaction of 75 if it is appropriate to do so. Show the predicted regression equation. (1 Mark)

Business School Salary Satisfaction ATAR G8 ATN VIC QLD SA NSW WA OTHER Australian Catholic University 37251 84 59 0 0 1 0 0 0 0 0 Australian National University 50385 80 82 1 0 0 0 0 0 0 1 Bond University 41729 86 50 0 0 0 1 0 0 0 0 Charles Darwin University 55675 83 60 0 0 0 0 0 0 0 1 Charles Sturt University 55136 79 65 0 0 1 0 0 0 0 0 CQUniversity 49456 84 52 0 0 0 1 0 0 0 0 Curtin University 42062 81 70 0 1 0 0 0 0 1 0 Deakin University 41551 86 53 0 0 1 0 0 0 0 0 Edith Cowan University 44343 89 55 0 0 0 0 0 0 1 0 Federation University Australia 41638 82 50 0 0 1 0 0 0 0 0 Flinders University 41464 84 60 0 0 0 0 1 0 0 0 Griffith University 40960 84 59 0 0 0 1 0 0 0 0 James Cook University 39881 81 49 0 0 0 1 0 0 0 0 La Trobe University 39612 82 50 0 0 1 0 0 0 0 0 Macquarie University 40692 80 80 0 0 0 0 0 1 0 0 Monash University 43928 85 82 1 0 1 0 0 0 0 0 Murdoch University 42078 76 70 0 0 0 0 0 0 1 0 Queensland University of Technology 43006 89 62 0 1 0 1 0 0 0 0 RMIT University 41897 75 70 0 1 1 0 0 0 0 0 Southern Cross University 44297 79 61 0 0 0 0 0 1 0 0 Swinburne University of Technology 39930 87 60 0 0 1 0 0 0 0 0 University of Adelaide 42946 80 80 1 0 1 0 0 0 0 0 University of Canberra 47485 82 68 0 0 0 0 0 0 0 1 University of Melbourne 57296 86 95 1 0 1 0 0 0 0 0 University of New England 55778 88 73 0 0 0 0 0 1 0 0 University of New South Wales 49665 78 96 1 0 0 0 0 1 0 0 University of Newcastle 45869 84 61 0 0 0 1 0 0 0 0 University of Notre Dame Australia 43728 84 70 0 0 0 0 0 0 1 0 University of Queensland 43860 83 81 0 0 0 1 0 0 0 0 University of South Australia 42939 88 65 0 1 0 0 1 0 0 0 University of Southern Queensland 52027 83 59 0 0 0 1 0 0 0 0 University of Sydney 52414 77 95 1 0 0 0 0 1 0 0 University of Tasmania 44345 75 65 1 0 0 0 0 0 0 1 University of Technology, Sydney 41782 84 69 0 1 0 0 0 1 0 0 University of the Sunshine Coast 34000 89 52 0 0 0 0 0 1 0 0 University of Western Australia 49003 79 80 1 0 0 0 0 0 1 0 University of Wollongong 46703 91 70 0 0 0 0 0 1 0 0 Victoria University 36321 73 50 0 0 1 0 0 0 0 0 Western Sydney University 40806 84 65 0 0 0 0 0 1 0 0

Explanation / Answer

a)

b)

p-value for the F-test is 0.05724 and since critical value is 0.05 and hence 0.05724>0.05, it is statistically significant

c)

The ranking of the unversities and also the location of the unversity would affect the payscale. For example, if a university is located in Sydney, it would have more number of students getting a job than a university located in some remote area.

e)

y=14813.5951+195.02(Satisfaction)+290.03(ATAR)-5432.102(VIC)

y=14813.5951+195.02(75)+290.03(80)-5432.102=47210.69

SUMMARY OUTPUT Regression Statistics Multiple R 0.632738048 R Square 0.400357437 Adjusted R Square 0.21426147 Standard Error 4924.743851 Observations 39 ANOVA df SS MS F Significance F Regression 9 469592055 52176895 2.151349341 0.057245791 Residual 29 703339958 24253102 Total 38 1172932013 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 14813.59505 18051.81706 0.820615177 0.41856015 -22106.5163 51733.7064 Satisfaction 195.0207213 205.6479236 0.948323318 0.350801067 -225.5765079 615.6179506 ATAR 290.0330503 101.9312145 2.845380109 0.008056709 81.56030891 498.5057917 G8 -1765.049936 3238.396557 -0.545038233 0.589894747 -8388.314567 4858.214694 ATN -2802.500179 2570.931944 -1.090071709 0.284656733 -8060.646398 2455.646041 VIC -5432.101999 2931.041329 -1.853301059 0.074039056 -11426.75461 562.5506084 QLD -3443.482402 3261.057241 -1.055940497 0.299713215 -10113.09334 3226.128531 SA -6109.692642 4648.841728 -1.314239761 0.199066309 -15617.64155 3398.256262 NSW -6536.68252 3262.19678 -2.003767081 0.054516098 -13208.62407 135.2590327 WA -5622.260506 3454.116869 -1.627698401 0.114406676 -12686.72271 1442.201703

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