Question

PLEASE INCLUDE EXCEL SCREENSHOTS IN YOUR ANSWER Introduction You...

PLEASE INCLUDE EXCEL SCREENSHOTS IN YOUR ANSWER

Introduction

You are back at it again as a quantitative analyst!This time a small college, Southwest College (SWC) has hired you to make sense of some data they have collected.The administrators have a lot of experience in education but precious little in data analysis.They have hired you to help them understand their data and make sound decisions.

SWC has provided you with as much information as they have, and it is up to you to determine the best quantitative approach to answering their questions.SWC has also made it clear that it is crucial that you explain what you are doing in a way such that a group of people unfamiliar with quantitative analysis can understand what you are doing and feel comfortable with the results.If you just provide a numerical answer to their questions, while still helpful, this will not meet their expectations for the project.

Deliverable

SWC has requested that you answer their questions in the form of a business report in MS Word format.Simply typing in answers to their questions below will be construed as a lack of professionalism. The writing must be free of errors and easy to understand.The exact design of the report is up to you, as long as the report format is used correctly and professionally, and all issues are addressed in an organized and coherent manner. You are to include any equations and calculations that you have done to be completely transparent.Any graphs or diagrams should be included in the body of the report or in an appendix.

THE CASE

The provost at SWC, based on anecdotal evidence, is convinced that the student-faculty ratio (# of students divided by the number of faculty) is an important determinant of student success after graduation.The university president believes the overall prestige of the university is a bigger factor, and other administrators believe it is largely the academic quality of the students admitted that matters most.SWC has purchased some data that shows students' starting salaries along with various characteristics of the universities the students attended. SWC wants to know if you can determine how the student starting salaries are related to the following variables in the data set: the per semester cost of attendance, the region of the country inwhich the school is located, the student-faculty ratio, average high school GPA of students admitted, the size of the school's library, and the school's national rank.Specifically, the administrators want answers to the following questions:

What is the appropriate quantitative technique to determine how the variables are related?

Which variables are important determinants of starting salaries?Be sure to explain how you are arriving at this conclusion.

What strategy would you recommend for improving the starting salaries of SWC graduates?

In addition to the questions above, SWC has requested a data visualization component in the report.You are to use multiple diagrams and appropriately formatted charts following the principles you learned in this course to help illustrate key findings.

OBS SALARY REGION COST TOTSTUD FACULTY HSGPA LIBVOL RANK

1 48670 North 9783 2310 50 3.15 216 128

2 51302 South 7954 2090 48 3.5 256 104

3 50949 East 19598 2970 86 3.25 424 34

4 54250 East 19340 3047 150 3.2 329 49

5 52089 West 9296 1650 62 3.38 332 95

6 49135 West 9863 1716 44 3.4 311 98

7 47136 South 6840 1661 44 3.16 220 124

8 46733 South 6844 1639 50 3.12 230 157

9 48515 East 5739 3542 111 3.12 230 145

10 51460 South 8778 770 48 3.66 157 91

11 54095 East 19514 2959 86 3.55 320 50

12 85890 East 19147 4191 141 3.42 470 23

13 52313 West 7518 1683 53 3.6 330 78

14 100750 West 13291 2959 88 3.7 600 5

15 97805 West 13853 1760 42 3.45 371 27

16 96100 West 14625 4609 125 3.55 542 19

17 97650 West 14031 3850 106 3.57 470 13

18 48515 West 18087 4125 88 3.2 208 115

19 44175 East 13893 1309 39 3.2 147 171

20 46655 North 14284 2882 34 3.25 215 131

21 52158 East 18323 2805 79 3.3 352 72

22 62504 North 20011 2420 92 3.3 305 55

23 108500 North 21457 1958 44 3.75 555 4

24 50840 North 12429 1474 56 3.37 339 90

25 45570 North 12740 3300 79 3.35 290 133

26 54250 West 13846 1837 68 3.31 280 65

27 121404 East 24401 3795 111 3.6 735 7

28 50840 East 18075 1463 105 3.29 383 84

29 104625 East 21307 2101 62 3.55 400 10

30 47585 West 14783 2068 56 3.2 198 112

31 46190 South 15600 2585 64 3.1 210 137

32 44795 North 15169 2035 30 3.2 208 141

33 65565 West 17328 3751 91 3.2 275 47

34 50995 North 16532 4103 120 3.27 312 82

35 45260 North 12990 1606 66 3 200 144

36 53475 North 14030 1705 31 3.3 190 76

37 48980 East 14523 1947 67 3.4 325 94

38 50065 West 15731 2574 72 3.23 240 88

39 93267 East 21048 1056 90 3.7 450 9

40 49744 East 11732 2200 64 3.3 192 89

41 71460 South 20164 2596 86 3.4 260 43

42 57660 South 13831 2200 75 3.53 530 59

43 52545 South 13466 2244 64 3.3 346 81

44 100564 East 21371 6017 206 3.3 410 22

45 45471 East 13888 1474 56 3 186 142

46 49290 East 19089 2761 55 3.27 260 127

47 94550 East 20261 5225 216 3.51 403 31

48 97193 East 21383 7073 270 3.52 728 18

49 71128 South 8259 2651 57 3.4 456 46

50 40300 South 8837 2145 45 3.12 221 175

51 52902 West 16109 2607 120 3.14 200 79

52 53320 West 14726 2134 47 3.16 197 74

53 105113 East 21227 6083 124 3.75 1745 1

54 47399 West 9300 836 40 3.42 231 139

55 79177 East 18747 3124 74 3.25 395 28

56 60450 South 8441 3410 124 3.3 400 48

57 45725 East 11492 1771 46 2.85 240 116

58 41850 West 8135 1056 24 3.25 146 132

59 62000 North 14225 2255 72 3.4 593 38

60 77500 North 14376 2299 59 3.49 510 30

61 48050 North 13321 2904 69 3.3 410 109

62 40300 South 7976 1936 42 3.15 161 172

63 97650 West 11371 2563 59 3.49 727 17

64 46500 North 14624 2860 207 3.2 280 113

65 55800 West 7709 3322 43 3.43 325 62

66 51150 South 11679 1485 53 3.3 329 92

67 46113 West 16075 2706 110 3.2 325 123

68 53863 South 4906 3124 52 3.35 540 83

69 52545 South 11407 1562 43 3.2 236 93

70 54250 North 16665 2706 169 3.24 285 73

71 60450 West 19852 2046 106 3.35 341 36

72 45942 South 16524 2475 67 3.1 230 155

73 44051 East 15927 1045 25 3.3 280 150

74 61225 North 14979 1859 56 3.2 220 40

75 58900 East 15394 2871 113 3.35 325 57

76 65100 West 16704 4807 97 3.24 285 37

77 46733 South 8828 1826 45 3.2 246 140

78 46500 South 15961 1705 54 3.1 252 105

79 61845 South 20217 5302 152 3.2 392 107

80 100750 North 22457 4191 107 3.67 750 2

81 77286 North 14681 2970 141 3.56 800 20

82 62916 South 7467 1870 35 3.3 260 54

83 53863 South 11982 1661 39 3 220 85

84 57195 West 13732 1749 63 3.28 245 96

85 46113 North 10906 847 30 3.2 124 122

86 52700 West 9929 1782 62 3.4 304 97

87 45725 East 13252 4422 113 3.07 242 114

88 45725 South 9425 1199 53 3.2 350 125

89 53785 East 18446 4917 165 3 377 86

90 87110 East 22096 4730 116 3.25 888 11

91 44640 North 7621 2200 95 3.22 250 163

92 44795 East 19098 2299 61 3.23 165 110

93 46500 North 7606 1298 39 3 200 160

94 43400 South 13463 1892 52 3.31 234 167

95 103850 North 21242 2233 122 3.6 557 14

96 82424 North 18372 1925 66 3.45 340 35

97 46033 North 19252 1529 45 3 225 136

98 64015 North 14398 2475 63 3.5 590 33

99 53940 South 10873 2343 44 3.28 262 80

100 41850 South 12508 2607 53 3.03 216 134

101 60450 West 14160 1639 44 3.5 291 53

102 40300 East 19206 2552 86 3.3 280 162

103 100750 East 22723 2618 102 3.7 540 8

104 38595 South 3125 1639 62 3.38 211 165

105 43400 West 16290 3355 72 3.3 301 129

106 46709 South 15651 1793 96 3.23 216 148

107 58280 East 12429 2442 41 3.22 450 64

108 61690 East 12505 2662 39 3.39 393 60

109 55800 East 17122 3355 69 3.2 409 70

110 54250 South 14961 2849 65 3.3 400 68

111 46035 South 16582 2959 76 3 268 151

112 63550 West 18497 3707 125 3.25 320 52

113 60450 West 18431 2651 100 3.17 245 56

114 60063 West 17403 3146 58 3.32 210 61

115 53785 East 18788 4994 163 3.16 316 87

116 46500 East 12522 2640 76 3.2 326 118

117 45958 West 7852 847 20 3.24 156 153

118 45725 South 14617 5104 98 3 290 168

119 80600 West 19688 2200 53 3.5 330 26

120 46578 North 10293 1397 36 3.3 302 106

121 60450 South 20593 2816 45 3.18 440 42

122 54095 West 18384 4510 86 3.15 340 75

123 97650 West 21749 1980 57 3.78 414 6

124 46500 South 19284 2387 91 3.2 316 146

125 44950 East 16459 5720 143 3.3 300 108

126 63550 East 20431 3245 83 3.2 319 51

127 63783 East 14871 4356 209 3.3 439 45

128 45723 South 8872 1859 205 3.1 345 117

129 92225 South 9592 5753 155 3.5 850 12

130 41850 South 10770 2530 50 2.73 300 170

131 55025 South 5104 2552 64 3.1 260 101

132 46188 North 9727 3135 56 3.01 305 121

133 45880 North 12161 2552 64 3.1 260 154

134 38750 East 17056 3146 72 2.8 310 174

135 55800 South 9808 2376 62 3 260 100

136 75950 West 10144 1364 61 3.55 264 29

137 54250 North 15994 1925 46 3.3 215 69

138 88350 South 19827 2057 83 3.62 329 16

139 45987 East 17983 1793 58 3.2 175 152

140 57350 East 17848 2508 81 3.41 420 63

141 99200 East 17354 4180 118 3.6 700 15

142 46035 East 15801 1815 74 3.31 250 111

143 54250 West 8076 1628 65 3.27 251 102

144 75950 West 11313 1628 76 3.63 450 25

145 79810 East 15914 1375 53 3.47 297 16

146 64325 West 19720 2310 95 3.2 476 41

147 54250 North 7377 2574 73 3.35 415 67

148 43245 East 13509 2761 65 3.08 301 135

149 45927 West 19035 2717 44 3 230 156

150 46113 East 16212 7469 227 3.1 481 138

151 55800 East 14749 2002 43 3.2 244 66

152 76448 East 14904 1958 55 3.34 300 17

153 77345 North 12603 3135 52 3.4 450 21

154 48825 West 8288 869 19 3.4 174 143

155 106950 East 21991 1111 110 3.82 850 3

156 46190 North 14606 3597 39 3.15 200 120