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 3,500
3.4 3,800
3.6 4,200
3.1 3,700
3.4 4,200
3.1 2,500

The estimated regression equation for these data is = 2090.5 + 581.1x and MSE = 21,284.
Required:
a. Develop a point estimate of the starting salary for a student with a GPA of 3.0
b. Develop a 95% confidence interval for the mean starting salary 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).

1.) 3833.8

2.) (3428.81 ; 4238.79)

Step-by-step explanation:

1.)

Point estimate of the salary for student with GPA of 3.

Using the regression model given :

Y = 2090.5 + 581.1x

x = 3

Y = 2090.5 + 581.1(3)

= 3833.8

2.)

95% confidence interval :

Y ± Tcritical * √MSE

Y = point estimate at x =3 ; = 3833.8

MSE = 21,284

Tcritical at 95% ; df = n-2 = 6-2 = 4

Tcritical(0.025 ; 4) = 2.776

√MSE = √21284 = 145.89036

Lower boundary : 3833.8 - 2.776(145.89036) = 3428.81

Upper boundary : 3833.8 + 2.776(145.89036) = 4238.79

(3428.81 ; 4238.79)

let's solve your equation step-by-step.

4x+2=2x+12

step 1: subtract 2x from both sides.

4x+2−2x=2x+12−2x

2x+2=12

step 2: subtract 2 from both sides.

2x+2−2=12−2

2x=10

step 3: divide both sides by 2.

2x

2

=

10

2

x=5

step-by-step explanation: