Chapter 3

Question 1

Least Squares Regression Line (LSRL)

Answer 1

ŷ = a + bx

Question 2

slope (LSRL)

Answer 2

b

Question 3

y-intercept (LSRL)

Answer 3

a

Question 4

CDOFS

Answer 4

Context
Direction (+ or -)
Outliers
Form (linear or nonlinear)
Strength (fairly, moderate, strong, weak)

Question 5

Correlation coefficient (r)

Answer 5

describes the strength of the relationship between two variables (not necessarily linear)

Question 6

falls between -1 and 1

Answer 6

r

Question 7

Coefficient of determination (r²)

Answer 7

Describes the strength of the relationship between two variables

Question 8

STEM r²

Answer 8

STEM: r²% of the variation in (response variable) can be explained by the linear regression model

Question 9

What happens to r and r² when there are outliers?

Answer 9

affected by outliers (gets smaller/weaker)

Question 10

falls between 0 and 100%

Answer 10

r squared

Question 11

STEM: residual: y - ŷ = actual y - predicted y

Answer 11

STEM (positive): the actual (response variable) is greater than the predicted by (residual units)
STEM (negative): change to less than

Question 12

Standard deviation of the residuals (s)

Answer 12

describes the average residual length

Question 13

larger s

Answer 13

weaker correlation

Question 14

STEM: s

Answer 14

The average error when using the line for prediction is ____(s)_ (units).