The following data are the monthly salaries y and the grade point averages x for students who obtained a bachelor's degre in business administration. GPA Monthly Salery (S) 2.6 3,600 3.5 3,800 3.6 4,200 3.1 3,000 3.5 4,100 2.9 2,400 The estimated regression equation for these data is y - 490 + 987.5x and MSE =333,719. a. Develop a point estimate of the starting salary for a student with a GPA of 3.0 (to 1 decimal). 3452.5 b. Develop a 95% confidence interval for the mean starting salanry for all students with a 3.0 GPA (to 2 decimals). C. Develop a 95% prediction interval for Ryan Dailey, a student with a GPA of 3.0 (to 2 decimals).

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Chapter4: Linear Functions
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Parts a, b, and c please

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
Monthly Salary ($)
2.6
3,600
3.5
3,800
3.6
4,200
3,800
3.5
4,100
2.9
2,400
The estimated regression equation for these data is y - 490 + 987.5x and MSE =333,719.
a. Develop a point estimate of the starting salary for a student with a GPA of 3.0 (to 1 decimal).
3452.5
b. Develop a 95% confidence interval for the mean starting salanry for all students with a 3.0 GPA (to 2 decimals).
C. Develop a 95% prediction interval for Ryan Dailey, a student with a GPA of 3.0 (to 2 decimals).
Transcribed Image Text:The following data are the monthly salaries y and the grade point averages x for students who obtained a bachelor's degree in business administration. GPA Monthly Salary ($) 2.6 3,600 3.5 3,800 3.6 4,200 3,800 3.5 4,100 2.9 2,400 The estimated regression equation for these data is y - 490 + 987.5x and MSE =333,719. a. Develop a point estimate of the starting salary for a student with a GPA of 3.0 (to 1 decimal). 3452.5 b. Develop a 95% confidence interval for the mean starting salanry for all students with a 3.0 GPA (to 2 decimals). C. Develop a 95% prediction interval for Ryan Dailey, a student with a GPA of 3.0 (to 2 decimals).
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