Question

A group of high school seniors took a scholastic aptitude test. The resulting math scores had a mean 526.8 with a standard deviation of 152.9, verbal scores had a mean 531.6 with a standard deviation of 148.8, and the correlation between verbal and math scores was r = 0.61. Complete parts a through f below. a) What is the correlation? The correlation is . (Round to three decimal places as needed.) b) Write the equation of the line of regression predicting verbal scores from math scores. y? = + x (Round to three decimal places as needed.) c) In general, what would a positive residual mean in this context? A. A positive residual means the student has the exact verbal score that the linear model would predict. B. A positive residual means the student has a lower verbal score than the linear model would predict. C. A positive residual means the student has a higher verbal score than the linear model would predict. d) A person tells you her math score was 547. Predict her verbal score. The student is expected to have a verbal score of . (Round to three decimal places as needed.) e) Using the predicted verbal score from part (d) and the regression equation math? = 193.487 + 0.627(verbal), predict the student's math score. The predicted math score is . (Round to three decimal places as needed.)

          A group of high school seniors took a scholastic aptitude test. The resulting math scores had a mean 526.8 with a standard deviation of 152.9, verbal scores had a mean 531.6 with a standard deviation of 148.8, and the correlation between verbal and math scores was r = 0.61. Complete parts a through f below.
a) What is the correlation?
The correlation is .
(Round to three decimal places as needed.)
b) Write the equation of the line of regression predicting verbal scores from math scores.
y? =  +  x
(Round to three decimal places as needed.)
c) In general, what would a positive residual mean in this context?
A. A positive residual means the student has the exact verbal score that the linear model would predict.
B. A positive residual means the student has a lower verbal score than the linear model would predict.
C. A positive residual means the student has a higher verbal score than the linear model would predict.
d) A person tells you her math score was 547. Predict her verbal score.
The student is expected to have a verbal score of .
(Round to three decimal places as needed.)
e) Using the predicted verbal score from part (d) and the regression equation math? = 193.487 + 0.627(verbal), predict the student's math score.
The predicted math score is .
(Round to three decimal places as needed.)

A group of high school seniors took a scholastic aptitude test. The resulting math scores had a mean 526.8 with a standard deviation of 152.9, verbal scores had a mean 531.6 with a standard deviation of 148.8, and the correlation between verbal and math scores was r = 0.61. Complete parts a through f below.
a) What is the correlation?
The correlation is .
(Round to three decimal places as needed.)
b) Write the equation of the line of regression predicting verbal scores from math scores.
y? = + x
(Round to three decimal places as needed.)
c) In general, what would a positive residual mean in this context?
A. A positive residual means the student has the exact verbal score that the linear model would predict.
B. A positive residual means the student has a lower verbal score than the linear model would predict.
C. A positive residual means the student has a higher verbal score than the linear model would predict.
d) A person tells you her math score was 547. Predict her verbal score.
The student is expected to have a verbal score of .
(Round to three decimal places as needed.)
e) Using the predicted verbal score from part (d) and the regression equation math? = 193.487 + 0.627(verbal), predict the student's math score.
The predicted math score is .
(Round to three decimal places as needed.)

Added by Marcos M.

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