One student in the sample was 73 inches tall with a foot


1. What is the correlation between SAT Math and SAT Verbal?

2. What is the slope of the regression equation when using SAT Math as the response variable (Y) and SAT Verbal as the predictor variable (X)?

A) Correlation = 0.711; Slope = 153.3

B) Correlation = 0.787; Slope = 107.3

C) Correlation = 0.672; Slope = 198.7

D) Correlation = 0.711; Slope = 0.7162

2.If the correlation between a response variable Y and explanatory variable X is - 0.8, what is the value that defines how much variation in Y is explained by X?

A) 64%

B) - 8%

C) 8%

D) - 64%

3.Which of the following variables would typically NOT be used as the response variable for linear regression?

A) Gender

B) GPA

C) Height

D) Age

4. Describe the type of association shown in the scatterplot above:

A) Positive linear association

B) Positive curvilinear association

C) Negative linear association

D) Negative curvilinear association

5.In the simple linear regression equation y = b0 + b1x, the symbol x represents the

A) estimated or predicted response.

B) explanatory variable.

C) estimated slope.

D) estimated intercept.

6.A regression between foot length (response variable in cm) and height (explanatory variable in inches) for 33 students resulted in the following regression equation:

• y = 10.9 + 0.23x

One student in the sample was 73 inches tall with a foot length of 29 cm. What is the predicted foot length for this student?

A) 27.69 cm

B) 17.57 cm

C) 29 cm

D) 33 cm

7.A study is conducted comparing a student's height versus the height of their father. The correlation between father's heights and student's heights for 79 male students was r = 0.669. What is the proportion of variation in son's heights explained by the linear relationship with father's heights?

A) ± 82.0%

B) 82.0%

C) 44.8%

D) ± 44.8%

8.The correlation between two variables is given by r = 0.0. What does this mean?

A) There is a perfect negative relationship between the two variables.

B) All of the points must fall exactly on a horizontal straight line.

C) There is a perfect positive relationship between the two variables

D) The best straight line through the data is horizontal

9.Based on the p-value for HEIGHT, we can reject the null hypothesis and conclude that there exists a linear relationship between Height and Weight.

A) True

B) False

10.Which variable in the Regression Equation represents the independent variable (also known as the predictor or explanatory variable)?

A) Height

B) Weight

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Mathematics: One student in the sample was 73 inches tall with a foot
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