## 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?

ATTACHMENT PREVIEW

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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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