a. Use information in Figure 2 and choose the correct regression equation  b. Use Figure 3 to find value of s and r2 ,value of linear correlation coefficient r is c. Based on your answer in part (b), the weekly exercise time in minutes is an excellent predictor of change in cholesterol level before and after exercise program. Based on your answer in part (b), the linear dependance between weekly exercise time and change in cholesterol level is strong negative

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a. Use information in Figure 2 and choose the correct regression equation 

b. Use Figure 3 to find value of s and r,value of linear correlation coefficient r is

c. Based on your answer in part (b), the weekly exercise time in minutes is an excellent predictor of change in cholesterol level before and after exercise program. Based on your answer in part (b), the linear dependance between weekly exercise time and change in cholesterol level is strong negative

ANOVA
Sum of
Squares
Model
df
Mean Square
Sig.
1
Regression 642950.535
642950.535
.000
1
876.722
Residual
35201.145
48
733.357
Total
678151.680
49
a. Dependent Variable: Change
b. Predictors: (Constant), ExerciseTime
Figure 3: Analysis of Variance
Transcribed Image Text:ANOVA Sum of Squares Model df Mean Square Sig. 1 Regression 642950.535 642950.535 .000 1 876.722 Residual 35201.145 48 733.357 Total 678151.680 49 a. Dependent Variable: Change b. Predictors: (Constant), ExerciseTime Figure 3: Analysis of Variance
Physicians have been recommending more exercise for their patients, particularly those
who are overweight. One benefit of regular exercise appears to be a reduction in choles-
terol, a substance associated with heart disease. In order to study the relationship more
carefully, a physician took a random sample of 50 patients who do not exercise. He
measured their cholesterol levels. He then started these patients on regular exercise
programs. After four months, the physician asked each patient how many minutes per
week (on average) he or she exercised. He also measured their cholesterol levels. The
independent variable is Exercise Time (as in weekly exercise time in minutes). The
response variable is Change (as in change in cholesterol level before and after exercise
program).
300
200
100
-100
-200
100
200
300
400
500
Exercise Time
Figure 1: Scatter plot and fitted regression line
Coefficients
Standardized
Coefficients
Unstandardized Coefficients
Model
B
Std. Error
Beta
Sig.
1
(Constant)
-239.772
10.130
-23.669
.000
ExerciseTime
.981
.033
.974
29.609
.000
a. Dependent Variable: Change
Figure 2: Estimated regression coefficients
Change
Transcribed Image Text:Physicians have been recommending more exercise for their patients, particularly those who are overweight. One benefit of regular exercise appears to be a reduction in choles- terol, a substance associated with heart disease. In order to study the relationship more carefully, a physician took a random sample of 50 patients who do not exercise. He measured their cholesterol levels. He then started these patients on regular exercise programs. After four months, the physician asked each patient how many minutes per week (on average) he or she exercised. He also measured their cholesterol levels. The independent variable is Exercise Time (as in weekly exercise time in minutes). The response variable is Change (as in change in cholesterol level before and after exercise program). 300 200 100 -100 -200 100 200 300 400 500 Exercise Time Figure 1: Scatter plot and fitted regression line Coefficients Standardized Coefficients Unstandardized Coefficients Model B Std. Error Beta Sig. 1 (Constant) -239.772 10.130 -23.669 .000 ExerciseTime .981 .033 .974 29.609 .000 a. Dependent Variable: Change Figure 2: Estimated regression coefficients Change
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