These are the values in simcha’s data set. (1, 18), (2, 22), (3, 38), (4, 45),  (5, 77) simcha determines the equation of a linear regression line to be yˆ=14.1x−2.3 . use the point tool to graph the residual plot for the data set. round residuals to the nearest unit as needed.

The residual points are (1,6.2)(2,-3.9)(3,-2)(4,-9.1)(5,8.8).

Refer the attached figure.

Step-by-step explanation:

Given : These are the values in Simcha’s data set (1, 18), (2, 22), (3, 38), (4, 45), (5, 77) . Simcha determines the equation of a linear regression line to be yˆ=14.1x−2.3 .

To find : Use the point tool to graph the residual plot for the data set. Round residuals to the nearest unit as needed.

Solution :

A residual is defined as the difference between the predicted value and the actual value i.e. Residual=Actual - Predicted

We have given a linear regression line which gives you predicted output i.e. yˆ=14.1x−2.3

Now, we find the residual value.

1) (1,18)

Actual = 18          

Predicted = y=14.1(1)-2.3=11.8

Residual = 18-11.8 =6.2

The residual at x = 1 is 6.2.

2) (2,22)

Actual = 22

Predicted = y=14.1(2)-2.3=25.9

Residual = 22-25.9=-3.9

The residual at x = 2 is -3.9

3) (3,38)

Actual = 38

Predicted = y=14.1(3)-2.3=40

Residual = 38-40=-2

The residual at x = 3 is -2.

4) (4,45)

Actual = 45

Predicted = y=14.1(4)-2.3=54.1

Residual = 45-54.1=-9.1

The residual at x = 4 is -9.1.

5) (5,77)

Actual = 77

Predicted = y=14.1(5)-2.3=68.2

Residual = 77-68.2=8.8

The residual at x =5 is 8.8

Therefore, The residual points are (1,6.2)(2,-3.9)(3,-2)(4,-9.1)(5,8.8).

Refer the attached figure below showing the residual points.

The data points shown in red color.

The residual points shown in blue color.

ian gonna lie that is way to much