Q1:- Which of the following statements accurately describe the least squares regression line (LSRL)? Check all that apply.

Group of answer choices

Relative to other lines, the LSRL goes through more of the data points.

Relative to other lines, the LSRL gives the smallest predictions.

Relative to other lines, the LSRL has the smallest sum of squared errors (SSE).

Here is a scatterplot with its least squares regression line.

Q2:-If there is scatter in the data about the line, there is prediction error. Which value of x has the largest absolute prediction error?

Group of answer choices

https://www.cuyamaca.edu/academics/departments/math/math-160-canvas-pics/lmc/mod9-2of4-qz-q2.jpg

x=2

x=3

x=4

Q 3:-Here is a scatterplot with its least squares regression line.

LSR line y = 4 + .6x

The least squares regression line is y = 4 + 0.6 x, with an SSE of 20.

Here is another line that fits the data pretty well: y = 3.5 + 0.7x.

What do we know about the SSE of the line y = 3.5 + 0.7x?

https://www.cuyamaca.edu/academics/departments/math/math-160-canvas-pics/lmc/mod9-2of4-qz-q2.jpg

Group of answer choices

less than 20

equal to 20

greater than 20

impossible to tell with the information given

Q4:-What is the SSE of the line pictured?

https://www.cuyamaca.edu/academics/departments/math/math-160-canvas-pics/lmc/mod9-2of4-qz-q4.jpg

Group of answer choices

-10

0

10

impossible to tell