Deck 10: Correlation and Regression

Question 1

Consider the following linear regression prediction equation: Y = 12 + 3X. If X = 7, what is the predicted value of Y for this observation?

A) 3
B) 12
C) 21
D) 33

Answer 1

33

Question 2

Based on the equation in question 1, where does the regression line cross the y-axis?

A) 3
B) 12
C) 21
D) 33

Answer 2

12

Question 3

Based on the equation in question 1, what type of correlation appears to exist in the data?

A) positive
B) negative
C) symmetrical
D) There is no correlation.

Answer 3

positive

Question 4

Consider the following linear regression prediction equation: Y = 4 + (-4.2)X. If X=2, what is the predicted value of Y for this observation?

A) -7.8
B) -4.4
C) 4
D) 12.4

Question 5

Based on the equation in question 4, where does the regression line cross the y-axis?

A) -7.8
B) -4.4
C) 4
D) 12.4

Question 6

Based on the equation in question 4, what type of correlation appears to exist in the data?

A) positive
B) negative
C) symmetrical
D) There is no correlation.

Question 7

In the linear regression equation, Y=a+bx, the coefficient, "b" represents -----------.

A) the predicted value of y
B) the y-intercept
C) slope
D) Pearson's r

Question 8

In the linear regression equation, Y=a+bx, "a" represents -----------.

A) the predicted value of y
B) the y-intercept
C) slope
D) Pearson's r

Question 9

If r² =.60, what percent of the variation in the dependent variable is left unexplained
By the independent variable?

A) .4
B) .6
C) 40
D) 60

Question 10

If r² =.40, what percent of the variation in the dependent variable is explained by the independent variable?

A) .4
B) .6
C) 40
D) 60

Question 11

Use the data below to answer questions:


-What is the sum of squares for the independent variable?

A) 0
B) 28
C) 30
D) 34

Question 12

Use the data below to answer questions:


-What is the sum of squares for the dependent variable?

A) 0
B) 28
C) 34
D) 50

Question 13

Use the data below to answer questions:


-What is the sum of products?

A) 0
B) 28
C) 34
D) 50

Question 14

Use the data below to answer questions:


-What is the value of Pearson's r?

A) 0
B) .34
C) .91
D) 1

Question 15

Use the data below to answer questions:


-What is the t-ratio?

A) 0
B) 3.8
C) 4.6
D) 34

Question 16

Use the data below to answer questions:


-How many degrees of freedom exist in the data?

A) 0
B) 2
C) 3
D) 5

Question 17

Use the data below to answer questions:


-What is the slope?

A) -1.2
B) 0
C) 1.2
D) 5

Question 18

Use the data below to answer questions:


-What is the y-intercept?

A) -1.2
B) 0
C) 1.2
D) 5

Question 19

Use the data below to answer questions:


-What is the predicted value of Y when X equals 5?

A) -1.2
B) 1.2
C) 4.8
D) 5

Question 20

Use the data below to answer questions:


-Y is predicted to be 10.8 when X equals --------------?

A) 4.8
B) 10
C) 10.8
D) 12

Question 21

Use the data below to answer questions:


-What is the direction of the relationship between these variables?

A) positive
B) negative
C) symmetrical
D) There is no correlation.

Question 22

A relationship is said to be strong when Pearson's r is .10.

Question 23

A Pearson's r of -.9 represents a stronger association than an r of .60.

Question 24

In the linear regression equation, "a" represents the y-intercept.

Question 25

In the linear regression equation, "b" represents the y-intercept.

Question 26

r² represents the percent of total variance in the independent variable that is explained by the dependent variable.

Question 27

Use the data below to answer the following questions:
a. Create a scatterplot using the data below.
b. Calculate the slope and the y-intercept for the regression line for the distribution. Write the regression line equation.
Slope:
Y-intercept:
Regression line:
c.Interpret the numbers of boththe slope and the y-intercept.
d.Compute r and ² for the regression equation.
e. Interpret both the r and ² What does each number tell us?

Question 28

Use the table below to answer the following questions:
a.Calculate the slope and the y-intercept for the regression line for the distribution. Writethe regression line.
Slope:
Y-intercept:
Regression line:
b.Interpret the numbers of both the slope and the y-intercept.
c.Compute r and r² for the regression equation.
d. Interpret both the r and r² . What does each number tell us?