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I am trying to understand results from a regression analysis. Attached are the results. There is no page requirement. I just don’t understand fully how to read the results and need to add them to a pr

Regression Statistics R 0.95218 R-square 0.90664 Adjusted R0.87997 S 519,195.72 N 10 Enrollment = 1,255,008.97414 – 1,021.30038 * Tuition Costs -…

I am trying to understand results from a regression analysis. Attached are the results. There is no page requirement. I just don’t understand fully how to read the results and need to add them to a project for class. 1. What are the results of your regression analysis?  2. What are the implications of the t-stats, F test and Adjusted R2?  Are they consistent or contradictory?  If they seem to be contradictory, how can this be resolved? 3. What are key take-a-ways that can be applied in your own personal or professional real-world settings?  Provide concrete or hypothetical examples (if you are not in an applicable field) that support your conclusions.  How might this model change in the future given assumptions?

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Regression StaTsTcs
R
0.95218
R-square
0.90664
Adjusted R-
0.87997
S
519,195.72
N
10
Enrollment =
1,255,008.97414 – 1,021.30038 * ±uiTon Costs – 8.86787 * Financial Aid
ANOVA
d.f.
SS
MS
F
p-level
Regression
2
1.83E+13
9.16E+12
33.98956
0.00025
Residual
7
1.89E+12
2.70E+11
Total
9
2.00E+13
Coe±cient
Standard Error
LCL
UCL
t Stat
p-level
H0 (5%)
H0 (1%)
Intercept
1,255,008.97
2,976,291.61
-5,782,802.34
8,292,820.29
0.42167
0.68591 accepted
accepted
Tui±on Cos
-1,021.30
223.70142
-1,550.27
-492.33058
-4.56546
0.00259 rejected
rejected
Financial A
-8.86787
23.52699
-64.50037
46.76463
-0.37692
0.7174 accepted
accepted
T (5%)
2.36462
T (1%)
3.49948
LCL – Lower value of a reliable interval (LCL)
UCL – Upper value of a reliable interval (UCL)
Residuals
ObservaTon Enrollment
Predicted Y
Residual
Standardized StudenTzed Deleted t
Leverage
Cook’s D
DFI²
PRESS
1
20,427,711
19,597,628.99
830,082.01
1.59878
1.9751
2.74824
0.34476
0.68417
1.99347
1,266,830.92
2
19,102,814
19,047,144.96
55,669.04
0.10722
0.14043
0.13019
0.417
0.0047
0.11011
95,487.15
3
18,248,128
18,843,529.45
-595,401.45
-1.14678
-1.36812
-1.47984
0.2974
0.2641
-0.96279
-847,425.92
4
17,758,870
18,119,226.01
-360,356.01
-0.69407
-1.39044
-1.5131
0.75083
1.94192
-2.62658
-1,446,226.39
5
17,487,475
17,914,409.36
-426,934.36
-0.8223
-0.87283
-0.85601
0.11244
0.03217
-0.30468
-481,021.29
6
17,272,044
17,414,418.77
-142,374.77
-0.27422
-0.28924
-0.2694
0.10113
0.00314
-0.09036
-158,393.46
7
16,911,481
16,580,495.97
330,985.03
0.6375
0.69861
0.67058
0.1673
0.03268
0.30057
397,482.53
8
16,611,711
16,141,078.64
470,632.36
0.90646
1.01483
1.01737
0.20217
0.08699
0.51213
589,889.16
9
15,927,987
15,723,048.38
204,938.62
0.39472
0.4725
0.4446
0.30212
0.03222
0.29253
293,660.37
10
15,312,289
15,679,529.47
-367,240.47
-0.70733
-0.84836
-0.82921
0.30485
0.10521
-0.54912
-528,289.96
Minimum
15,312,289
15,679,529.47
-595,401.45
-1.14678
-1.39044
-1.5131
0.10113
0.00314
-2.62658
-1,446,226.39
Maximum
20,427,711
19,597,628.99
830,082.01
1.59878
1.9751
2.74824
0.75083
1.94192
1.99347
1,266,830.92
Mean
17,506,051
17,506,051
5.59E-10
0
-0.04675
0.00634
0.3
0.31873
-0.13247
-81,800.69

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