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Inorganic Chemistry

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INDIAN INSTITUTE OF MANAGEMENT ROHTAK/KOZHIKODE

Model fit: if regression is possible

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.634a

.402

.374

.8372

a. Predictors: (Constant), A9, A2, A7, A4, A3, A6, A1, A8, A5

Interpretation:

R-Square = % of variation in the dependent variable (DV) is explained by the independent variable (IV). Looking at the above table, one can say that 40.4% variation in the DV is explained by the IV. Thus DV and IV are correlated, so regression analysis is possible.  

ANOVAa

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

89.666

9

9.963

14.214

.000b

Residual

133.173

190

.701

Total

222.840

199

a. Dependent Variable: Vibrancy

b. Predictors: (Constant), A9, A2, A7, A4, A3, A6, A1, A8, A5

Interpretation:

One can rely on ANOVA table for model fit summary. Comparing Sig. value and alpha (5%) (refer above ANOVA table), one can accept alternative hypothesis describes that DV and IV are associated. Thus regression is possible.

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

1.317

.393

3.349

.001

A1

.155

.072

.169

2.174

.031

A2

-.024

.051

-.031

-.480

.632

A3

.152

.063

.172

2.416

.017

A4

-.041

.048

-.055

-.866

.388

A5

-.052

.055

-.076

-.946

.345

A6

.120

.053

.158

2.256

.025

A7

.152

.065

.172

2.346

.020

A8

.215

.064

.247

3.372

.001

A9

.044

.048

.065

.929

.354

a. Dependent Variable: Vibrancy

...

...

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