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Mind lap-Cer age.com/static/nb/uifindexhtml?nbld 5914688nbl QSearch Cristina Con

ID: 3362804 • Letter: M

Question

Mind lap-Cer age.com/static/nb/uifindexhtml?nbld 5914688nbl QSearch Cristina Conti at 1159 PM EST Check My Work The following data are the monthly salaries y and the grade point averages x for students who obtained a bachelor's degree in business administration. GPA 2.7 3.5 3.7 3.1 3.4 2.8 Monthly Salary($) 3,600 3,800 4,200 3,800 4,100 2,400 The estimated regression equation for these data is y- 30+1,150x and MSE-264,250. a. Develop a point estimate of the starting salary for a student with a GPA of 3.0 (to 1 decimal). 3420 b. Develop a 95% confidence interval for the mean starting salary for all students with a 3.0 GPA (to 2 decimals). s2833.51 4017.60 3) c. Develop a 95% prediction rter al for Ryan Daley, a student with a GPA of 3.0 (to 2 decimals artially Correct Check My Work

Explanation / Answer

Result:

95% CI= (2755.66, 4084.34)

95% PI = (1845.72, 4994.28)

Regression Analysis

0.500

n

6

r

0.707

k

1

Std. Error

514.053

Dep. Var.

salary

ANOVA table

Source

SS

df

MS

F

p-value

Regression

1,058,000.0000

1  

1,058,000.0000

4.00

.1160

Residual

1,057,000.0000

4  

264,250.0000

Total

2,115,000.0000

5  

Regression output

confidence interval

variables

coefficients

std. error

   t (df=4)

p-value

95% lower

95% upper

Intercept

-30.0000

1,851.0650

-0.016

.9878

-5,169.3804

5,109.3804

gpa

1,150.0000

574.7282

2.001

.1160

-445.7013

2,745.7013

Predicted values for: salary

95% Confidence Interval

95% Prediction Interval

gpa

Predicted

lower

upper

lower

upper

Leverage

3

3,420.000

2,755.657

4,084.343

1,845.718

4,994.282

0.217

Regression Analysis

0.500

n

6

r

0.707

k

1

Std. Error

514.053

Dep. Var.

salary

ANOVA table

Source

SS

df

MS

F

p-value

Regression

1,058,000.0000

1  

1,058,000.0000

4.00

.1160

Residual

1,057,000.0000

4  

264,250.0000

Total

2,115,000.0000

5  

Regression output

confidence interval

variables

coefficients

std. error

   t (df=4)

p-value

95% lower

95% upper

Intercept

-30.0000

1,851.0650

-0.016

.9878

-5,169.3804

5,109.3804

gpa

1,150.0000

574.7282

2.001

.1160

-445.7013

2,745.7013

Predicted values for: salary

95% Confidence Interval

95% Prediction Interval

gpa

Predicted

lower

upper

lower

upper

Leverage

3

3,420.000

2,755.657

4,084.343

1,845.718

4,994.282

0.217