Sum of Mean F Ratio Source DE Prob > F Squares 8.35409 Square Model 1 88.3541 3.07 0.1104 10 287.89591 28.7896 C. Total 376.25000 11 Parameter Estimates Std Tern Estimate Prob > t Error Ratio Intercept 6.8725681 2.257651 3.04 0.0124 BHI Change 5.077821 2.898557 1.75 0.1104 (a) What does the scatterplot suggest about the relationship between depression score change and BMI change? The scatterplot suggests that there -Select- va linear relationship between depression score change and BMI change because there is -Select-- ] trend in the plot. (b) What is the equation of the estimated regression line? (c) Is there is a useful linear relationship between the two variables? Carry out an appropriate test using a significance level of a = 0.05. State the null and alternative hypotheses. O Ho: ß = 0 versus H, ß = 0 O Hg: B = 0 versus H: B >0 O H: B = 0 versus H: B< 0 O Hạ: Bso versus H: B >0 O Hạ: B=0 versus H: B = 0 Report the test statistic and its P-value for whether there is a useful linear relationship between the two sets of data. (Round your test statistic to two decimal places and your P-value to four decimal places.) P-value = Use the P-value to evaluate the statistical significance of the results at the 5% level. O H, is not rejected. There is sufficient evidence of a useful linear relationship between depression score change and BMI change. O H, is rejected. There is not evidence of a useful linear relationship between depression score change and BMI change. O H, is rejected. There is sufficient evidence of a useful linear relationship between depression score change and BMI change. O H, is not rejected. There is not sufficient evidence of a useful linear relationship between depression score change and BMI change.

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ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
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Question
Analysis of Variance
Sum of
Mean
Source
DF
F Ratio
Prob > F
Squares
Square
Model
1.
88.35409
88.3541
3.07
0.1104
Error
10
287.89591
28.7896
C. Total
11
376.25000
Parameter Estimates
Std
Term
Estimate
Prob > t||
Error
Ratio
Intercept
6.8725681
2.257651
3.04
0.0124*
BMI Change
5.077821
2.898557
1.75
0.1104
(a) What does the scatterplot suggest about the relationship between depression score change and BMI change?
The scatterplot suggests that there --Select--
va linear relationship between depression score change and BMI change because there is ---Select---
trend in the plot.
(b) What is the equation of the estimated regression line?
ý =
(c) Is there is a useful linear relationship between the two variables? Carry out an appropriate test using a significance level of a = 0.05.
State the null and alternative hypotheses.
O Ho: B = 0 versus H: B # 0
O Ho: B = 0 versus H: B > 0
O Ho: B = 0 versus H: B < 0
O H: B SO versus H: B > 0
O Ho: B + 0 versus H: B = 0
Report the test statistic and its P-value for whether there is a useful linear relationship between the two sets of data. (Round your test statistic to two decimal places and your P-value to four decimal places.)
t =
P-value =
Use the P-value to evaluate the statistical significance of the results at the 5% level.
O H, is not rejected. There is sufficient evidence of a useful linear relationship between depression score change and BMI change.
O H, is rejected. There is not evidence of a useful linear relationship between depression score change and BMI change.
O H, is rejected. There is sufficient evidence of a useful linear relationship between depression score change and BMI change.
O H, is not rejected. There is not sufficient evidence of a useful linear relationship between depression score change and BMI change.
Transcribed Image Text:Analysis of Variance Sum of Mean Source DF F Ratio Prob > F Squares Square Model 1. 88.35409 88.3541 3.07 0.1104 Error 10 287.89591 28.7896 C. Total 11 376.25000 Parameter Estimates Std Term Estimate Prob > t|| Error Ratio Intercept 6.8725681 2.257651 3.04 0.0124* BMI Change 5.077821 2.898557 1.75 0.1104 (a) What does the scatterplot suggest about the relationship between depression score change and BMI change? The scatterplot suggests that there --Select-- va linear relationship between depression score change and BMI change because there is ---Select--- trend in the plot. (b) What is the equation of the estimated regression line? ý = (c) Is there is a useful linear relationship between the two variables? Carry out an appropriate test using a significance level of a = 0.05. State the null and alternative hypotheses. O Ho: B = 0 versus H: B # 0 O Ho: B = 0 versus H: B > 0 O Ho: B = 0 versus H: B < 0 O H: B SO versus H: B > 0 O Ho: B + 0 versus H: B = 0 Report the test statistic and its P-value for whether there is a useful linear relationship between the two sets of data. (Round your test statistic to two decimal places and your P-value to four decimal places.) t = P-value = Use the P-value to evaluate the statistical significance of the results at the 5% level. O H, is not rejected. There is sufficient evidence of a useful linear relationship between depression score change and BMI change. O H, is rejected. There is not evidence of a useful linear relationship between depression score change and BMI change. O H, is rejected. There is sufficient evidence of a useful linear relationship between depression score change and BMI change. O H, is not rejected. There is not sufficient evidence of a useful linear relationship between depression score change and BMI change.
A papert gave data on
x = change in Body Mass Index (BMI in kilograms/meter2) and
y = change in a measure of depression
for patients suffering from depression who participated in a pulmonary rehabilitation program. JMP output for these data is shown below.
Bivariate Fit of Depression Score Change by BMI Change
20
15
10
-0.5
0.5
1.5
BMI change
- Linear Fit
Linear Fit
Depression score change = 6.8725681 + 5.077821*BMI Change
Summary of Fit
RSquare
0.234828
RSquare Adj
0.158311
Root Mean Square Error
5.365593
Mean of Response
9.75
Observations (or Sum Wgts)
12
Analysis of Variance
Sum of
Mean
Source
DF
F Ratio
Prob > F
Squares
Square
Model
1
88.35409
88.3541
3.07
0.1104
Error
10
287.89591
28.7896
C. Total
11
376.25000
Depression score change
Transcribed Image Text:A papert gave data on x = change in Body Mass Index (BMI in kilograms/meter2) and y = change in a measure of depression for patients suffering from depression who participated in a pulmonary rehabilitation program. JMP output for these data is shown below. Bivariate Fit of Depression Score Change by BMI Change 20 15 10 -0.5 0.5 1.5 BMI change - Linear Fit Linear Fit Depression score change = 6.8725681 + 5.077821*BMI Change Summary of Fit RSquare 0.234828 RSquare Adj 0.158311 Root Mean Square Error 5.365593 Mean of Response 9.75 Observations (or Sum Wgts) 12 Analysis of Variance Sum of Mean Source DF F Ratio Prob > F Squares Square Model 1 88.35409 88.3541 3.07 0.1104 Error 10 287.89591 28.7896 C. Total 11 376.25000 Depression score change
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