The Head of production at Amiba private limited needed to examine the key determinants of company profitability($,000). So, he collected relevant(monthly) data and following is the summary of his regression output.   SUMMARY OUTPUT     Regression Statistics Multiple R 0.5776 R Square 0.3336 Adjusted R Square 0.2670 Standard Error 2.2743 Observations 34   ANOVA             df SS MS F Significance F Regression 3 77.6774 25.8925 5.0060 0.0062 Residual 30 155.1693 5.1723     Total 33 232.8467           Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper  95.0% Intercept 10.49 2.9211 3.5927 0.0012 4.5291 16.4605 4.5291 16.4605 Variable X 0.99 1.2461 0.7937 0.4336 -1.5559 3.5340 -1.5559 3.5340 Variable Y 2.56 1.1291 2.2663 0.0308 0.2529 4.8648 0.2529 4.8648 Variable Z 2.06 1.2777 1.6107 0.1177 -0.5515 4.6674 -0.5515 4.6674     Interpret the meaning of intercept coefficients and at 5% level review the significance of those variables to the model      Calculate the adjusted R square and interpret its meaning                                                                                                                                                                ANSWER b(i):

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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  1. The Head of production at Amiba private limited needed to examine the key determinants of company profitability($,000). So, he collected relevant(monthly) data and following is the summary of his regression output.

 

SUMMARY OUTPUT

   

Regression Statistics

Multiple R

0.5776

R Square

0.3336

Adjusted R Square

0.2670

Standard Error

2.2743

Observations

34

 

ANOVA

         

 

df

SS

MS

F

Significance F

Regression

3

77.6774

25.8925

5.0060

0.0062

Residual

30

155.1693

5.1723

   

Total

33

232.8467

 

 

 

 

 

Coefficients

Standard Error

t Stat

P-value

Lower

95%

Upper

95%

Lower

95.0%

Upper

 95.0%

Intercept

10.49

2.9211

3.5927

0.0012

4.5291

16.4605

4.5291

16.4605

Variable X

0.99

1.2461

0.7937

0.4336

-1.5559

3.5340

-1.5559

3.5340

Variable Y

2.56

1.1291

2.2663

0.0308

0.2529

4.8648

0.2529

4.8648

Variable Z

2.06

1.2777

1.6107

0.1177

-0.5515

4.6674

-0.5515

4.6674

 

 

  1. Interpret the meaning of intercept coefficients and at 5% level review the significance of those variables to the model     
  2. Calculate the adjusted R square and interpret its meaning                                                                                                                                                               

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