Use the SPSS output to fill in the blanks below.
Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.949a
.900
.892
6.95922
a. Predictors: (Constant), Exercise
ANOVAa
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
5254.545
1
5254.545
108.496
.000b
Residual
581.169
12
48.431
Total
5835.714
13
a. Dependent Variable: Weight
b. Predictors: (Constant), Exercise
Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
B
Std. Error
Beta
1
(Constant)
156.949
6.614
23.695
.000
Exercise
7.727
1.562
.328
1.471
.000
a. Dependent Variable: Weight
A was used to test the hypothesis that would predict . The independent variable predicted the dependent variable, F(1,43) = , p . The slope of the regression line is . The y-intercept of the regression line is . The expected weight of someone who spends zero hours excercising is approximately