Question

Regression Statistics Multiple R 0.3641 R Square 0.1325 Adjusted R Square 0.1176 Standard Error 0.0834 Observations...

Regression Statistics
Multiple R 0.3641
R Square 0.1325
Adjusted R Square 0.1176
Standard Error 0.0834
Observations 60
ANOVA
df SS MS F Significance F
Regression 1 0.0617 0.0617 8.8622 0.0042
Residual 58 0.4038 0.0070
Total 59 0.4655
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept -0.0144 0.0110 -1.3062 0.1966 -0.0364 0.0077
X Variable 1 0.8554 0.2874 2.9769 0.0042 0.2802 1.4307

How do you interpret the above table?

Homework Answers

Answer #1

from the given O/p,

intercept = -0.0144

slope = 0.8554

so, regression equation is

Y^ = -0.0144 + 0.8554*x

for every unit increase in value of x, predicted value of y get increase by 0.8554

========

correlation coefficient = 0.3641

this indicates a weak positive correlation between x and y

========

R² = 0.1325

this indicates about 13.25% of variation in observation of Y is explained by variable x

============

F stat = 8.86

p value=0.042

So, this overall model of regression is significant

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