Question 1

R-sq is a measure of ...

Accepted Answer

A)  the probability that the regression line makes a correct prediction. 
B)  the initial predicted starting point of the response variable when x is zero. 
C)  the percentage of the accuracy of the regression equation. 
D)  the change in the y-variable that corresponds with the change in the x-variable. 
E)  the proportion of the variability in the response variable that is explained by the explanatory variable. 
A)  the probability that the regression line makes a correct prediction. 
B)  the initial predicted starting point of the response variable when x is zero. 
C)  the percentage of the accuracy of the regression equation. 
D)  the change in the y-variable that corresponds with the change in the x-variable. 
E)  the proportion of the variability in the response variable that is explained by the explanatory variable.

Question 2

The following scatterplot shows a relationship between x and y that results in a correlation
coefficient of $$r = 0 \text {. Explain why } r = 0$$ 
0 in this situation even though there appears to be a
strong relationship between the x and y variables.

Accepted Answer

The correlation coefficient on

Question 3

A regression model examining the amount of distance a long distance runner runs (in miles) to
Predict the amount of fluid the runner drinks (ounces) has a slope of 4.6. Which interpretation is
Appropriate?

Accepted Answer

A)  A runner drinks a minimum of 4.6 oz. 
B)  We predict 4.6 miles for every ounce that is drunk. 
C)  Each mile adds 4.6 more ounces. 
D)  We predict for every mile run, the runner drinks 4.6 more ounces. 
E)  The correlation is needed to interpret this value. 
A)  A runner drinks a minimum of 4.6 oz. 
B)  We predict 4.6 miles for every ounce that is drunk. 
C)  Each mile adds 4.6 more ounces. 
D)  We predict for every mile run, the runner drinks 4.6 more ounces. 
E)  The correlation is needed to interpret this value.

Question 4

The correlation between $X$ and $Y$ is $r = 0.35$. If we double each $X$ value, decrease each $Y$ by $0.20$, and interchange the variables (put $X$ on the $Y$-axis and vice versa), the new correlation

Accepted Answer

A)  is 0.35 
B)  cannot be determined. 
C)  is 0.70 
D)  is 0.90 
E)  is 0.50 
A)  is 0.35 
B)  cannot be determined. 
C)  is 0.70 
D)  is 0.90 
E)  is 0.50

Question 5

A company's sales increase by the same amount each year. This growth is . . .

Accepted Answer

A)  logarithmic 
B)  power 
C)  linear 
D)  exponential 
E)  quadratic 
A)  logarithmic 
B)  power 
C)  linear 
D)  exponential 
E)  quadratic

R-sq is a measure of ...

A regression model examining the amount of distance a long distance runner runs (in miles) to Predict the amount of fluid the runner drinks (ounces) has a slope of 4.6. Which interpretation is Appropriate?

The correlation between $X$ and $Y$ is $r = 0.35$ . If we double each $X$ value, decrease each $Y$ by $0.20$ , and interchange the variables (put $X$ on the $Y$ -axis and vice versa), the new correlation

A company's sales increase by the same amount each year. This growth is . . .

Exploring and Understanding Data

Gathering Data

Randomness and Probability

From the Data at Hand to the World at Large

Accessing Associations Between Variables

Inference When Variables Are Related

Regression, Associations, and Predictive Modeling

Filters

Exam 2: Exploring Relationships Between Variables

R-sq is a measure of ...

The following scatterplot shows a relationship between x and y that results in a correlation coefficient of r=0. Explain why r=0r = 0 \text {. Explain why } r = 0r=0. Explain why r=0 0 in this situation even though there appears to be a strong relationship between the x and y variables.

A regression model examining the amount of distance a long distance runner runs (in miles) to Predict the amount of fluid the runner drinks (ounces) has a slope of 4.6. Which interpretation is Appropriate?

The correlation between XXX and YYY is r=0.35r = 0.35r=0.35 . If we double each XXX value, decrease each YYY by 0.200.200.20 , and interchange the variables (put XXX on the YYY -axis and vice versa), the new correlation

A company's sales increase by the same amount each year. This growth is . . .

Exploring and Understanding Data

Gathering Data

Randomness and Probability

From the Data at Hand to the World at Large

Accessing Associations Between Variables

Inference When Variables Are Related

Regression, Associations, and Predictive Modeling

Filters

The correlation between $X$ and $Y$ is $r = 0.35$ . If we double each $X$ value, decrease each $Y$ by $0.20$ , and interchange the variables (put $X$ on the $Y$ -axis and vice versa), the new correlation