Model Summary
Model 
R 
R Square 
Adjusted R Square 
Std. Error of the Estimate 
1 
.816 
.666 
.629 
1.23721 
a. Predictors: (Constant),x
ANOVA
Model 
Sum of Squares 
df 
Mean Square 
F Sig 

Regression Residual Total 
27.500 13.776 41.276 
1 9 10 
27.500 1.531 
17.966 .002^{b} 
a. Dependent Variable: Y
b. Predictors: (Constant), X
Coefficients
Model 
Understand Coefficients B Std Error 
Standardized Coefficients Beta 
t 
Sig 

1 (Constant) x 
3.001 1.125 .500 .118 
.816 
2.667 4.239 
.026 .002 
a. Dependent Variable: Y
Using the information given above, answer the following questions:
a. find linear correlation coefficient, r ?
b. find r^{2} , interpretation for r^{2.}
c. Can the regression model be used for prediction of y? give reasons
d. Write down the regression equation, identifying the yintercept and slope values.
e. Give an interpretation of the slope (b_{1} ) value.
f. Predict the value of y, when x = 14. Give your answer to 2 decimal places.
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