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Do Homework - Matthew Crenshaw Google Chrome Secure https://www.mathxl.com/Student/playerHomework.aspx?homeworkId-450660528&questionId-14;&flush.; MAT-181-06 (FA17) Homework: HW #19-Chapter 10 Sections 2-3 Save Score: 0.75 of 1 pt 14 of 16 (16 complete) Score: 98.44%, 15.75 of 16 10.3.15 Question Help The data show systolic and diastolic blood pressure of certain people. Find the regression equation, letting the systolic reading be the independent (x) variable. Find the best predicted diastolic pressure for a person with a systolic reading of 125 Is the predicted value close to 76.0, which was the actual diastolic reading? Use a significance level of 0 05 148 115 136 115 127 128 140 145 82 83 97 60 65 93 101 108 Diastolic Click the icon to vew the critical values of the Pearson correlation coefficent r What is the regression equation? y2601 85 x (Round to two decimal places as needed ) What is the best predicted diastolic pressure for a person with a systolic reading of 125? y 86.1 (Round to one decimal place as needed) 76.0, which was the actual diastolic reading? You answered 80 8 Get answer teedback very close to the actual diastolic reading hot close to the actual diastolic reading C. The predicted value is close to the actual diastolic reading D. The predicted value is exactly the same as the actual diastolic reading

Explanation / Answer

Result:

The regression equation is

y= -26.01+0.85 x

Predicted value of y when x=125,

y = -26.01+0.85 *125

=80.2

The predicted value is not close to the actual diastolic reading.

Regression Analysis

r²

0.403

n

8

r

0.635

k

1

Std. Error

14.183

Dep. Var.

y

ANOVA table

Source

SS

df

MS

F

p-value

Regression

813.8977

1  

813.8977

4.05

.0910

Residual

1,206.9773

6  

201.1629

Total

2,020.8750

7  

Regression output

confidence interval

variables

coefficients

std. error

   t (df=6)

p-value

95% lower

95% upper

Intercept

-26.0120

55.9742

-0.465

.6585

-162.9759

110.9519

x

0.8511

0.4231

2.011

.0910

-0.1843

1.8865

Predicted values for: y

95% Confidence Interval

95% Prediction Interval

x

Predicted

lower

upper

lower

upper

Leverage

125

80.380

66.259

94.501

42.912

117.848

0.166

Regression Analysis

r²

0.403

n

8

r

0.635

k

1

Std. Error

14.183

Dep. Var.

y

ANOVA table

Source

SS

df

MS

F

p-value

Regression

813.8977

1  

813.8977

4.05

.0910

Residual

1,206.9773

6  

201.1629

Total

2,020.8750

7  

Regression output

confidence interval

variables

coefficients

std. error

   t (df=6)

p-value

95% lower

95% upper

Intercept

-26.0120

55.9742

-0.465

.6585

-162.9759

110.9519

x

0.8511

0.4231

2.011

.0910

-0.1843

1.8865

Predicted values for: y

95% Confidence Interval

95% Prediction Interval

x

Predicted

lower

upper

lower

upper

Leverage

125

80.380

66.259

94.501

42.912

117.848

0.166

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