Regression Lines and Correlation

Shown is a residual plot. Would a linear regression model of the data be most appropriate?

• YES

• NO

Shown is a residual plot. How many positive residuals are there?

• 5

• 1

• 3

• 9

• This residual plot represents a linear fit.
• This residual plot represents a nonlinear fit.
• This residual plot represents no fit.

What is the value of the correlation coefficient?

• 0.891

• -0.891

• 0.875

• 0.943

• -0.943

Which of these points appears to be an “Outlier?”

• A

• B

• C

• D

• y = –13.9916 + 1.9200 * x
• y = –3.4694 + 0.7800 * x
• y = 0.8052 + 0.3169 * x
• y = 1.4483 + 0.2472 * x

Which of the following statistics show how much variance there is between y–values and x–values?

• Coefficient of Determination

• Slope of the Regression Line

• Standard Deviation

• Variance

Base your answer to the following question on the following information. The table below displays the win/loss record of American League teams through 79 games in the 2006 season with the earned run averages of each team.
What is the correlation coefficient between wins and ERA?

• r = –0.66 

• r = –0.78

• r = –0.82

• r = –0.90

The slope of the LSRL for the points (1,2), (3,4) and (5,6). What is the yintercept?

• –7.5

• –3

• 1

• 3

What is the best definition of the least squares regression line?

• The line that minimizes the squares of the horizontal distances between the data points and the line.

• The line that minimizes the squares of the vertical distances between the data points and the line.

• The line that minimizes the vertical distances between the data points and the line.

• The line that passes through the most number of data points.