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5- Interpret the coefficient of determination (R-squared) and the F test. SUMMARY OUTPUT Regression Statistics Multiple...

5- Interpret the coefficient of determination (R-squared) and the F test.

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.8811

R Square

0.7764

Adjusted R Square

0.7205

Standard Error

14.7724

Observations

16

ANOVA

df

SS

MS

F

Regression

3

9091.7392

3030.5797

13.8874

Residual

12

2618.7008

218.2251

Total

15

11710.44

Coefficients

Standard Error

t Stat

P-value

Intercept

29.1385

174.7427

0.1668

0.8703

PFH

-2.1236

0.3405

-6.2361

0.0000

PR

1.0345

0.4667

2.2164

0.0467

M

3.0871

0.9993

3.0892

0.0094
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Answer #1

1. R-Square value of 0.7764 means the regression model is able to explain 77.64 percent of variation through independent variables PFH, PR and M

2. F value close to means the independent variables do not have significant variation, so a larger value of F value means that these independent variables have significantly different from zero and are not by chance. Hence the ANOVA is able to capture variation significantly.

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