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 The data set (found on the first tab of the provided spreadsheet, Case Report 2 Data ) contains the following variables the per semester cost of attendance, the region of the country in which the school is located, the total students enrolled, the number of faculty at the university, the average high school GPA of students admitted, the size of the school's library, and the school's national rank Additionally, the university provost has compiled historical enrollment data from SWC, which can be found on the second tab in the provided spreadsheet ( Enrollment data ) Specifically, the administrators want answers to the following questions What is the appropriate quantitative technique to determine how the variables are related Based on your analysis, how are students' starting salaries related to each of the explanatory variables in the data set Which variables are statistically important determinants of starting salaries How did you arrive at this answer In your opinion, are any important variables missing from the data set Based on your analysis, what strategy or strategies would you recommend for improving the starting salaries of SWC graduates Explain in detail, justifying with evidence from your analysis What techniques can SWC use to forecast enrollment for the next academic year Can you show us several techniques in detail Which forecasting method do you recommend given the historical enrollment data provided How is this determined 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 The data SWC has purchased and compiled can be found in the Excel file Case 2 Data located in the D2L course shell OBS SALARY REGION Cost TOTSTUD FACULTY HSGPA LIBVOL RANK 1 84630 East 32491 2 6855 75 360 3 04 460 6 50 2 120658 2 North 21173 04 7053 75 124 8 3 23 630 22 3 72056 4 South 26208 5816 25 153 6 2 945 294 138 4 166842 East 36944 88 2499 75 264 3 629 1190 4 5 157170 East 38174 64 5890 5 244 8 3 515 756 9 6 73532 16 South 11491 2 3737 25 105 6 3 002 308 125 7 97506 24 North 33618 48 5445 220 8 3 135 427 56 8 71936 28 East 27236 16 16805 25 544 8 2 945 673 4 139 9 162006 North 35686 56 5024 25 292 8 3 42 779 8 15 10 87048 East 28764 96 7548 75 165 6 3 04 572 6 71 11 76650 6 West 16569 84 3861 105 6 3 23 435 4 99 12 62868 South 14846 16 4826 25 108 2 964 309 4 176 13 152575 8 West 23273 04 3960 100 8 3 2775 519 4 28 14 72540 South 26814 48 3836 25 129 6 2 945 352 8 106 15 84388 2 West 30885 12 10147 5 206 4 2 9925 476 76 16 76408 8 East 24398 64 4380 75 160 8 3 23 455 95 17 84146 4 South 18266 64 5271 75 105 6 3 116 366 8 81 18 89224 2 West 23069 76 3935 25 151 2 3 116 343 97 19 145496 52 East 35360 64 2376 216 3 515 630 10 20 71646 12 West 31978 8 6113 25 105 6 2 85 322 157 21 118482 West 19005 84 3663 182 4 3 4485 630 26 22 84388 2 East 32783 52 6657 75 206 4 3 3725 448 51 23 69638 4 North 12803 28 4950 228 3 059 350 164 24 83421 North 23570 4 3836 25 74 4 3 135 266 77 25 82527 12 West 27063 12 5865 75 288 2 983 280 80 26 93698 28 West 29237 04 7078 5 139 2 3 154 294 62 27 125736 West 33075 84 4950 127 2 3 325 462 27 28 89949 6 South 23236 08 4950 180 3 3535 742 60 29 98148 96 South 12544 56 4207 5 84 3 135 364 55 30 133988 4 East 32166 96 9429 75 338 4 3 249 658 24 31 157170 West 22328 88 6657 75 211 2 3 515 840 6 32 72540 North 24568 32 6435 496 8 3 04 392 114 33 94302 South 14180 88 7672 5 297 6 3 135 560 49 34 74232 6 West 24835 44 4653 134 4 3 04 277 2 113 35 151621 08 East 35923 44 15914 25 648 3 344 1019 2 19 36 65286 West 13666 8 2376 57 6 3 0875 204 4 133 37 128581 44 North 30864 96 4331 25 158 4 3 2775 476 36 38 137826 South 33309 36 4628 25 199 2 3 439 460 6 17 39 95511 North 25164 72 4182 75 134 4 3 04 308 41 40 111477 6 South 33875 52 5841 206 4 3 23 364 44 41 87048 South 16477 44 5346 148 8 2 85 364 101 42 72053 28 North 16341 36 7053 75 134 4 2 8595 427 122 43 79310 4 North 20880 72 3316 5 134 4 3 2015 474 6 91 44 83179 2 West 24739 68 4801 5 112 8 3 002 275 8 75 45 79794 South 19620 72 3341 25 127 2 3 135 460 6 93 46 70122 East 27651 12 12870 343 2 3 135 420 109 47 189390 24 East 40993 68 8538 75 266 4 3 42 1029 8 48 75683 4 East 9641 52 7969 5 266 4 2 964 322 146 49 84630 North 12393 36 5791 5 175 2 3 1825 581 68 50 81366 48 East 30782 64 6311 25 189 6 3 135 492 8 73 51 71327 88 South 14904 96 4182 75 492 2 945 483 118 52 68719 56 East 26757 36 2351 25 60 3 135 392 151 53 87048 West 12951 12 7474 5 103 2 3 2585 455 63 54 119258 88 East 25038 72 4405 5 132 3 173 420 18 55 152334 West 23572 08 8662 5 254 4 3 3915 658 14 56 81970 2 South 22622 88 5049 153 6 3 135 484 4 82 57 100347 West 33129 6 5197 5 228 3 04 666 4 42 58 71331 South 24556 56 11484 235 2 2 85 406 169 59 76892 4 East 32069 52 6212 25 132 3 1065 364 128 60 76167 West 13923 84 1955 25 45 6 3 23 243 6 144 61 96236 4 East 21008 4 5989 5 93 6 3 2205 550 2 61 62 62868 South 13399 68 4356 100 8 2 9925 225 4 173 63 75683 4 West 30386 16 9281 25 211 2 3 04 291 2 116 64 71936 28 West 27006 6088 5 264 3 04 455 124 65 62868 East 32266 08 5742 206 4 3 135 392 163 66 71814 6 East 26545 68 4083 75 177 6 3 1445 350 112 67 78101 4 West 26428 08 5791 5 172 8 3 0685 336 89 68 71669 52 South 27760 32 5568 75 160 8 2 945 322 156 69 102281 4 West 29111 04 8439 75 218 4 3 04 385 48 70 71331 East 22263 36 9949 5 271 2 2 9165 338 8 115 71 79552 2 North 27773 76 9231 75 288 3 1065 436 8 83 72 83904 6 East 31563 84 11236 5 391 2 3 002 442 4 88 73 79310 4 East 30366 3291 75 252 3 1255 536 2 85 74 72903 48 South 14831 04 4108 5 108 3 04 344 4 141 75 91884 East 25861 92 6459 75 271 2 3 1825 455 58 76 60450 East 28654 08 7078 5 172 8 2 66 434 175 77 71814 6 South 27857 76 6657 75 182 4 2 85 375 2 152 78 124503 6 East 26735 52 3093 75 127 2 3 2965 415 8 17 79 84630 North 26869 92 4331 25 110 4 3 135 301 70 80 94302 West 23788 8 3687 75 105 6 3 325 407 4 54 81 94302 South 34596 24 6336 108 3 021 616 43 82 156879 84 East 35903 28 13538 25 494 4 3 135 574 23 83 82212 West 16680 72 4009 5 148 8 3 23 425 6 98 84 77600 64 East 19709 76 4950 153 6 3 135 268 8 90 85 73942 44 West 15624 1881 96 3 249 323 4 140 86 81970 2 South 19163 76 3514 5 103 2 3 04 330 4 94 87 84026 28 South 20129 76 3737 25 93 6 2 85 308 86 88 83904 6 East 30989 28 11063 25 396 2 85 527 8 87 89 69880 2 East 32084 64 5172 75 146 4 3 0685 231 111 90 120900 North 24151 68 5172 75 141 6 3 3155 714 31 91 94302 West 30964 08 5964 75 240 3 0115 343 57 92 79480 44 East 32924 64 6682 5 206 4 3 0875 593 6 35 93 85839 South 8574 72 5742 153 6 2 945 364 102 94 157170 North 37727 76 9429 75 256 8 3 4865 1050 3 95 71811 48 North 32343 36 3440 25 108 2 85 315 137 96 90916 8 East 20880 72 5494 5 98 4 3 059 630 65 97 84630 South 25134 48 6410 25 156 3 135 560 69 98 65286 South 18093 6 5692 5 120 2 5935 420 171 99 118482 West 17041 92 3069 146 4 3 3725 369 6 30 100 72540 East 21036 96 5940 182 4 3 04 456 4 119 101 71936 28 North 18322 08 1905 75 72 3 04 173 6 123 102 163215 East 35795 76 4727 25 148 8 3 3725 560 11 103 68913 East 23340 24 2945 25 93 6 3 04 205 8 172 104 80277 6 South 14747 04 1732 5 115 2 3 477 219 8 92 105 71572 8 North 20430 48 5742 153 6 2 945 364 155 106 89466 East 29984 64 5643 194 4 3 2395 588 64 107 152334 West 36538 32 4455 136 8 3 591 579 6 7 108 99863 4 North 24188 64 5568 75 151 2 3 325 826 34 109 72903 48 South 11497 92 3687 75 120 2 964 322 158 110 101556 West 28062 72 10815 75 232 8 3 078 399 38 111 74958 North 22379 28 6534 165 6 3 135 574 110 112 123516 12 East 31494 96 7029 177 6 3 0875 553 29 113 72781 8 North 23997 12 6484 5 81 6 3 0875 301 132 114 67704 West 27367 2 7548 75 172 8 3 135 421 4 130 115 99138 West 31074 96 8340 75 300 3 0875 448 53 116 72661 68 North 17292 24 3143 25 86 4 3 135 422 8 107 117 69880 2 North 25483 92 4578 75 72 3 04 291 2 142 118 81258 84 West 15617 28 3712 5 148 8 3 211 464 8 96 119 169260 North 36047 76 4405 5 105 6 3 5625 777 5 120 72056 4 North 24538 08 8093 25 93 6 2 9925 280 121 121 65286 South 21013 44 5865 75 127 2 2 8785 302 4 135 122 87048 East 24778 32 4504 5 103 2 3 04 341 6 67 123 84026 28 South 8242 08 7029 124 8 3 1825 756 84 124 84630 West 23261 28 4133 25 163 2 3 1445 392 66 125 75925 2 North 16435 44 5197 5 120 2 9925 302 4 129 126 80031 12 South 13362 72 4702 5 115 2 3 325 358 4 105 127 72540 South 32397 12 5370 75 218 4 3 04 442 4 147 128 67462 2 East 22695 12 6212 25 156 2 926 421 4 136 129 143871 South 16114 56 12944 25 372 3 325 1190 13 130 70934 76 East 23331 84 3316 5 134 4 2 85 260 4 143 131 84630 West 13567 68 3663 156 3 1065 351 4 103 132 81608 28 West 12630 24 3786 75 127 2 3 42 462 79 133 96720 North 23898 5073 75 172 8 3 23 830 2 39 134 72866 04 South 26293 68 4034 25 230 4 3 0685 302 4 149 135 72540 North 12778 08 2920 5 93 6 2 85 280 161 136 147498 East 34038 48 11756 25 518 4 3 3345 564 2 32 137 71694 48 West 13191 36 1905 75 48 3 078 218 4 154 138 70605 6 North 21823 2 3613 5 158 4 2 85 280 145 139 60208 2 South 5250 3687 75 148 8 3 211 295 4 166 140 99138 East 34324 08 7301 25 199 2 3 04 446 6 52 141 154752 East 29154 72 9405 283 2 3 42 980 16 142 120566 16 North 24664 08 6682 5 338 4 3 382 1120 21 143 71089 2 North 21403 2 7425 189 6 3 1825 406 134 144 71331 South 15834 2697 75 127 2 3 04 490 126 145 163976 28 East 35661 36 13686 75 297 6 3 5625 2443 2 146 67704 South 22617 84 4257 124 8 3 1445 327 6 168 147 96478 2 South 33964 56 11929 5 364 8 3 04 548 8 108 148 110959 68 South 13875 12 5964 75 136 8 3 23 638 4 47 149 135891 6 East 37121 28 10642 5 278 4 3 0875 1243 2 12 150 94302 West 33351 36 4603 5 254 4 3 1825 477 4 37 151 71331 East 19306 56 3984 75 110 4 2 7075 336 117 152 99501 48 East 24983 28 9801 501 6 3 135 614 6 46 153 152334 West 19103 28 5766 75 141 6 3 3155 1017 8 18 154 84630 North 27997 2 6088 5 405 6 3 078 399 74 155 149916 West 24570 10370 25 300 3 3725 758 8 20 156 71739 72 East 30211 44 4034 25 139 2 3 04 245 153 Second tab Enrollment data Year Fall Census 2005 5770 2006 6759 2007 6859 2008 7524 2009 7585 2010 8185 2011 7971 2012 8675 2013 8280 2014 8810 2015 8422 2016 9498 2017 8296 2018 9263 2019 7998 2020 8064 2021 7479

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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

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. The data set (found on the first tab of the provided spreadsheet, "Case Report #2 Data") contains the following variables: the per semester cost of attendance, the region of the country in which the school is located, the total students enrolled, the number of faculty at the university, the average high school GPA of students admitted, the size of the school's library, and the school's national rank. Additionally, the university provost has compiled historical enrollment data from SWC, which can be found on the second tab in the provided spreadsheet ("Enrollment data"). Specifically, the administrators want answers to the following questions:

What is the appropriate quantitative technique to determine how the variables are related?
Based on your analysis, how are students' starting salaries related to each of the explanatory variables in the data set?
Which variables are statistically important determinants of starting salaries? How did you arrive at this answer?
In your opinion, are any important variables missing from the data set?
Based on your analysis, what strategy or strategies would you recommend for improving the starting salaries of SWC graduates? Explain in detail, justifying with evidence from your analysis.
What techniques can SWC use to forecast enrollment for the next academic year?Can you show us several techniques in detail?
Which forecasting method do you recommend given the historical enrollment data provided?How is this determined?

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. The data SWC has purchased and compiled can be found in the Excel file "Case 2 Data" located in the D2L course shell.

OBS	SALARY	REGION	Cost	TOTSTUD	FACULTY	HSGPA	LIBVOL	RANK
1	84630	East	32491.2	6855.75	360	3.04	460.6	50
2	120658.2	North	21173.04	7053.75	124.8	3.23	630	22
3	72056.4	South	26208	5816.25	153.6	2.945	294	138
4	166842	East	36944.88	2499.75	264	3.629	1190	4
5	157170	East	38174.64	5890.5	244.8	3.515	756	9
6	73532.16	South	11491.2	3737.25	105.6	3.002	308	125
7	97506.24	North	33618.48	5445	220.8	3.135	427	56
8	71936.28	East	27236.16	16805.25	544.8	2.945	673.4	139
9	162006	North	35686.56	5024.25	292.8	3.42	779.8	15
10	87048	East	28764.96	7548.75	165.6	3.04	572.6	71
11	76650.6	West	16569.84	3861	105.6	3.23	435.4	99
12	62868	South	14846.16	4826.25	108	2.964	309.4	176
13	152575.8	West	23273.04	3960	100.8	3.2775	519.4	28
14	72540	South	26814.48	3836.25	129.6	2.945	352.8	106
15	84388.2	West	30885.12	10147.5	206.4	2.9925	476	76
16	76408.8	East	24398.64	4380.75	160.8	3.23	455	95
17	84146.4	South	18266.64	5271.75	105.6	3.116	366.8	81
18	89224.2	West	23069.76	3935.25	151.2	3.116	343	97
19	145496.52	East	35360.64	2376	216	3.515	630	10
20	71646.12	West	31978.8	6113.25	105.6	2.85	322	157
21	118482	West	19005.84	3663	182.4	3.4485	630	26
22	84388.2	East	32783.52	6657.75	206.4	3.3725	448	51
23	69638.4	North	12803.28	4950	228	3.059	350	164
24	83421	North	23570.4	3836.25	74.4	3.135	266	77
25	82527.12	West	27063.12	5865.75	288	2.983	280	80
26	93698.28	West	29237.04	7078.5	139.2	3.154	294	62
27	125736	West	33075.84	4950	127.2	3.325	462	27
28	89949.6	South	23236.08	4950	180	3.3535	742	60
29	98148.96	South	12544.56	4207.5	84	3.135	364	55
30	133988.4	East	32166.96	9429.75	338.4	3.249	658	24
31	157170	West	22328.88	6657.75	211.2	3.515	840	6
32	72540	North	24568.32	6435	496.8	3.04	392	114
33	94302	South	14180.88	7672.5	297.6	3.135	560	49
34	74232.6	West	24835.44	4653	134.4	3.04	277.2	113
35	151621.08	East	35923.44	15914.25	648	3.344	1019.2	19
36	65286	West	13666.8	2376	57.6	3.0875	204.4	133
37	128581.44	North	30864.96	4331.25	158.4	3.2775	476	36
38	137826	South	33309.36	4628.25	199.2	3.439	460.6	17
39	95511	North	25164.72	4182.75	134.4	3.04	308	41
40	111477.6	South	33875.52	5841	206.4	3.23	364	44
41	87048	South	16477.44	5346	148.8	2.85	364	101
42	72053.28	North	16341.36	7053.75	134.4	2.8595	427	122
43	79310.4	North	20880.72	3316.5	134.4	3.2015	474.6	91
44	83179.2	West	24739.68	4801.5	112.8	3.002	275.8	75
45	79794	South	19620.72	3341.25	127.2	3.135	460.6	93
46	70122	East	27651.12	12870	343.2	3.135	420	109
47	189390.24	East	40993.68	8538.75	266.4	3.42	1029	8
48	75683.4	East	9641.52	7969.5	266.4	2.964	322	146
49	84630	North	12393.36	5791.5	175.2	3.1825	581	68
50	81366.48	East	30782.64	6311.25	189.6	3.135	492.8	73
51	71327.88	South	14904.96	4182.75	492	2.945	483	118
52	68719.56	East	26757.36	2351.25	60	3.135	392	151
53	87048	West	12951.12	7474.5	103.2	3.2585	455	63
54	119258.88	East	25038.72	4405.5	132	3.173	420	18
55	152334	West	23572.08	8662.5	254.4	3.3915	658	14
56	81970.2	South	22622.88	5049	153.6	3.135	484.4	82
57	100347	West	33129.6	5197.5	228	3.04	666.4	42
58	71331	South	24556.56	11484	235.2	2.85	406	169
59	76892.4	East	32069.52	6212.25	132	3.1065	364	128
60	76167	West	13923.84	1955.25	45.6	3.23	243.6	144
61	96236.4	East	21008.4	5989.5	93.6	3.2205	550.2	61
62	62868	South	13399.68	4356	100.8	2.9925	225.4	173
63	75683.4	West	30386.16	9281.25	211.2	3.04	291.2	116
64	71936.28	West	27006	6088.5	264	3.04	455	124
65	62868	East	32266.08	5742	206.4	3.135	392	163
66	71814.6	East	26545.68	4083.75	177.6	3.1445	350	112
67	78101.4	West	26428.08	5791.5	172.8	3.0685	336	89
68	71669.52	South	27760.32	5568.75	160.8	2.945	322	156
69	102281.4	West	29111.04	8439.75	218.4	3.04	385	48
70	71331	East	22263.36	9949.5	271.2	2.9165	338.8	115
71	79552.2	North	27773.76	9231.75	288	3.1065	436.8	83
72	83904.6	East	31563.84	11236.5	391.2	3.002	442.4	88
73	79310.4	East	30366	3291.75	252	3.1255	536.2	85
74	72903.48	South	14831.04	4108.5	108	3.04	344.4	141
75	91884	East	25861.92	6459.75	271.2	3.1825	455	58
76	60450	East	28654.08	7078.5	172.8	2.66	434	175
77	71814.6	South	27857.76	6657.75	182.4	2.85	375.2	152
78	124503.6	East	26735.52	3093.75	127.2	3.2965	415.8	17
79	84630	North	26869.92	4331.25	110.4	3.135	301	70
80	94302	West	23788.8	3687.75	105.6	3.325	407.4	54
81	94302	South	34596.24	6336	108	3.021	616	43
82	156879.84	East	35903.28	13538.25	494.4	3.135	574	23
83	82212	West	16680.72	4009.5	148.8	3.23	425.6	98
84	77600.64	East	19709.76	4950	153.6	3.135	268.8	90
85	73942.44	West	15624	1881	96	3.249	323.4	140
86	81970.2	South	19163.76	3514.5	103.2	3.04	330.4	94
87	84026.28	South	20129.76	3737.25	93.6	2.85	308	86
88	83904.6	East	30989.28	11063.25	396	2.85	527.8	87
89	69880.2	East	32084.64	5172.75	146.4	3.0685	231	111
90	120900	North	24151.68	5172.75	141.6	3.3155	714	31
91	94302	West	30964.08	5964.75	240	3.0115	343	57
92	79480.44	East	32924.64	6682.5	206.4	3.0875	593.6	35
93	85839	South	8574.72	5742	153.6	2.945	364	102
94	157170	North	37727.76	9429.75	256.8	3.4865	1050	3
95	71811.48	North	32343.36	3440.25	108	2.85	315	137
96	90916.8	East	20880.72	5494.5	98.4	3.059	630	65
97	84630	South	25134.48	6410.25	156	3.135	560	69
98	65286	South	18093.6	5692.5	120	2.5935	420	171
99	118482	West	17041.92	3069	146.4	3.3725	369.6	30
100	72540	East	21036.96	5940	182.4	3.04	456.4	119
101	71936.28	North	18322.08	1905.75	72	3.04	173.6	123
102	163215	East	35795.76	4727.25	148.8	3.3725	560	11
103	68913	East	23340.24	2945.25	93.6	3.04	205.8	172
104	80277.6	South	14747.04	1732.5	115.2	3.477	219.8	92
105	71572.8	North	20430.48	5742	153.6	2.945	364	155
106	89466	East	29984.64	5643	194.4	3.2395	588	64
107	152334	West	36538.32	4455	136.8	3.591	579.6	7
108	99863.4	North	24188.64	5568.75	151.2	3.325	826	34
109	72903.48	South	11497.92	3687.75	120	2.964	322	158
110	101556	West	28062.72	10815.75	232.8	3.078	399	38
111	74958	North	22379.28	6534	165.6	3.135	574	110
112	123516.12	East	31494.96	7029	177.6	3.0875	553	29
113	72781.8	North	23997.12	6484.5	81.6	3.0875	301	132
114	67704	West	27367.2	7548.75	172.8	3.135	421.4	130
115	99138	West	31074.96	8340.75	300	3.0875	448	53
116	72661.68	North	17292.24	3143.25	86.4	3.135	422.8	107
117	69880.2	North	25483.92	4578.75	72	3.04	291.2	142
118	81258.84	West	15617.28	3712.5	148.8	3.211	464.8	96
119	169260	North	36047.76	4405.5	105.6	3.5625	777	5
120	72056.4	North	24538.08	8093.25	93.6	2.9925	280	121
121	65286	South	21013.44	5865.75	127.2	2.8785	302.4	135
122	87048	East	24778.32	4504.5	103.2	3.04	341.6	67
123	84026.28	South	8242.08	7029	124.8	3.1825	756	84
124	84630	West	23261.28	4133.25	163.2	3.1445	392	66
125	75925.2	North	16435.44	5197.5	120	2.9925	302.4	129
126	80031.12	South	13362.72	4702.5	115.2	3.325	358.4	105
127	72540	South	32397.12	5370.75	218.4	3.04	442.4	147
128	67462.2	East	22695.12	6212.25	156	2.926	421.4	136
129	143871	South	16114.56	12944.25	372	3.325	1190	13
130	70934.76	East	23331.84	3316.5	134.4	2.85	260.4	143
131	84630	West	13567.68	3663	156	3.1065	351.4	103
132	81608.28	West	12630.24	3786.75	127.2	3.42	462	79
133	96720	North	23898	5073.75	172.8	3.23	830.2	39
134	72866.04	South	26293.68	4034.25	230.4	3.0685	302.4	149
135	72540	North	12778.08	2920.5	93.6	2.85	280	161
136	147498	East	34038.48	11756.25	518.4	3.3345	564.2	32
137	71694.48	West	13191.36	1905.75	48	3.078	218.4	154
138	70605.6	North	21823.2	3613.5	158.4	2.85	280	145
139	60208.2	South	5250	3687.75	148.8	3.211	295.4	166
140	99138	East	34324.08	7301.25	199.2	3.04	446.6	52
141	154752	East	29154.72	9405	283.2	3.42	980	16
142	120566.16	North	24664.08	6682.5	338.4	3.382	1120	21
143	71089.2	North	21403.2	7425	189.6	3.1825	406	134
144	71331	South	15834	2697.75	127.2	3.04	490	126
145	163976.28	East	35661.36	13686.75	297.6	3.5625	2443	2
146	67704	South	22617.84	4257	124.8	3.1445	327.6	168
147	96478.2	South	33964.56	11929.5	364.8	3.04	548.8	108
148	110959.68	South	13875.12	5964.75	136.8	3.23	638.4	47
149	135891.6	East	37121.28	10642.5	278.4	3.0875	1243.2	12
150	94302	West	33351.36	4603.5	254.4	3.1825	477.4	37
151	71331	East	19306.56	3984.75	110.4	2.7075	336	117
152	99501.48	East	24983.28	9801	501.6	3.135	614.6	46
153	152334	West	19103.28	5766.75	141.6	3.3155	1017.8	18
154	84630	North	27997.2	6088.5	405.6	3.078	399	74
155	149916	West	24570	10370.25	300	3.3725	758.8	20
156	71739.72	East	30211.44	4034.25	139.2	3.04	245	153

Second tab: Enrollment data

Year	Fall Census
2005	5770
2006	6759
2007	6859
2008	7524
2009	7585
2010	8185
2011	7971
2012	8675
2013	8280
2014	8810
2015	8422
2016	9498
2017	8296
2018	9263
2019	7998
2020	8064
2021	7479