STT 200 Exam 2: Questions With Detailed Answers
All but one of the following statements below contains a mistake. which on
could be true?
A. The correlation between height and weight is 0.568 inches per pound
B. The correlation between height and weight is 0.568
C. The correlation between the breed of a dog and its weight is 0.435
D. The correlation between gender and age is -0.171
E. The correlation between blood alcohol level and reaction time is 0.73, then
the correlation between reaction time and blood alcohol level is -0.73 Right
Ans - B. the correlation between height and weight is 0.568
A correlation of zero between two quantitative variable means that:
A. We have done something wrong in our calculation of r
B. There is no association between the two variables
C. There is no linear association between the two variables
D. Re-expressing the data will guarantee a linear association between the two
variables
E. None of the above Right Ans - C. There is no linear association between
the two variables
A residual plot is useful because (I) it will help us to see whether a linear
model makes sense; (II) it might show a pattern in the data that was hard to
see in the original scatterplot
A. I only
B. II only
C. I and II
D. Neither I nor II
E. None of the above Right Ans - C. I and II
A regression analysis of students' college grade point averages (GPAs) and
their high school GPAs found the coefficient of determination, R^2=0.311.
which of these is true? I. High school GPA accounts for 31.1% of college GPA II.
31.1% of college GPAs can be correctly predicted with this model III. 31.1% of
the variance in college GPA can be accounted for by the model
A. I only
B. II only
C. III only
D. I and II only
, E. None of the above Right Ans - C. III only
Extrapolation is:
A. Okay to do as long as we are making predictions into the future
B. Okay to do is we tell people we are assuming the linear relationship will
hold outside of the range of the data
C. Okay to do as long as there were no outliers in the original data
D. Not okay to do
E. None of the above Right Ans - D. Not okay to do
When using the midterm exam scores to predict a student's final grade in a
class, the student would prefer to have a
A. Positive residual, because that means the student's final grade is higher
than what we would predict with the model
B. Positive residual, because that means the student's final grade is lower than
what we would predict with the model
C. Residual equal to zero, because that means the student's grade is exactly
what we would predict with the model
D. Negative residual, because that means the student's final grade is higher
than what we predict with the model
E. None of the above Right Ans - A. Positive residual, because that means
the student's final grade is higher than what we predict with the model
The correlation between two variables is given by r=0.0. what does this mean?
A. The best straight line through the data is horizontal
B. There is a perfect positive relationship between the two variables
C. There is a perfect negative relationship between the two variables
D. All of the points must fall exactly on a horizontal straight line
E. None of the above Right Ans - A. The best straight line through the data
is horizontal
If the correlation coefficient between two quantitative variables is positive,
what conclusion can we draw?
A. High values on the first variable are associated with high values on the
second variable
B. Low values on the first variable are associated with low values on the
second variable
C. High values on the first variable are associated with low values on the
second variable
All but one of the following statements below contains a mistake. which on
could be true?
A. The correlation between height and weight is 0.568 inches per pound
B. The correlation between height and weight is 0.568
C. The correlation between the breed of a dog and its weight is 0.435
D. The correlation between gender and age is -0.171
E. The correlation between blood alcohol level and reaction time is 0.73, then
the correlation between reaction time and blood alcohol level is -0.73 Right
Ans - B. the correlation between height and weight is 0.568
A correlation of zero between two quantitative variable means that:
A. We have done something wrong in our calculation of r
B. There is no association between the two variables
C. There is no linear association between the two variables
D. Re-expressing the data will guarantee a linear association between the two
variables
E. None of the above Right Ans - C. There is no linear association between
the two variables
A residual plot is useful because (I) it will help us to see whether a linear
model makes sense; (II) it might show a pattern in the data that was hard to
see in the original scatterplot
A. I only
B. II only
C. I and II
D. Neither I nor II
E. None of the above Right Ans - C. I and II
A regression analysis of students' college grade point averages (GPAs) and
their high school GPAs found the coefficient of determination, R^2=0.311.
which of these is true? I. High school GPA accounts for 31.1% of college GPA II.
31.1% of college GPAs can be correctly predicted with this model III. 31.1% of
the variance in college GPA can be accounted for by the model
A. I only
B. II only
C. III only
D. I and II only
, E. None of the above Right Ans - C. III only
Extrapolation is:
A. Okay to do as long as we are making predictions into the future
B. Okay to do is we tell people we are assuming the linear relationship will
hold outside of the range of the data
C. Okay to do as long as there were no outliers in the original data
D. Not okay to do
E. None of the above Right Ans - D. Not okay to do
When using the midterm exam scores to predict a student's final grade in a
class, the student would prefer to have a
A. Positive residual, because that means the student's final grade is higher
than what we would predict with the model
B. Positive residual, because that means the student's final grade is lower than
what we would predict with the model
C. Residual equal to zero, because that means the student's grade is exactly
what we would predict with the model
D. Negative residual, because that means the student's final grade is higher
than what we predict with the model
E. None of the above Right Ans - A. Positive residual, because that means
the student's final grade is higher than what we predict with the model
The correlation between two variables is given by r=0.0. what does this mean?
A. The best straight line through the data is horizontal
B. There is a perfect positive relationship between the two variables
C. There is a perfect negative relationship between the two variables
D. All of the points must fall exactly on a horizontal straight line
E. None of the above Right Ans - A. The best straight line through the data
is horizontal
If the correlation coefficient between two quantitative variables is positive,
what conclusion can we draw?
A. High values on the first variable are associated with high values on the
second variable
B. Low values on the first variable are associated with low values on the
second variable
C. High values on the first variable are associated with low values on the
second variable
