Correlation and Regression 2

A researcher performs an experiment to find if there is a correlation between amount of time spent a day on a computer and the need for corrective lenses. There is a correlation coefficient of 0.73 found. Which of the following is true?

• 53.29% of the variance in the need for corrective lenses is explained by the relationship between the need for corrective lenses and the amount of time a day spent of a computer.
• The strength of the linear relationship between the need for corrective lenses and the amount of time a day spent on a computer is 0.5329.
• 73.00% of the variance in the need for corrective lenses is explained by the relationship between the need for corrective lenses and
• The strength of the linear relationship between the need for corrective lenses and the amount of time a day spent on a computer is 0.8544.

Tags

CCSS.HSS.ID.B.6B

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

Tags

CCSS.HSS.ID.B.6

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

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

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

• –7.5
• –3
• 1
• 3

Tags

CCSS.HSS.ID.C.8

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.

Tags

CCSS.HSS.ID.C.7

Base your answer to the following question on the least square regression line: y = 3.12 - 0.79 * x
The mean of the y–variable is 2.12. What is the mean of the x–variable?

• 1.27
• 1.45
• 1.68
• 1.69

Tags

CCSS.8.EE.C.8C

Which of the following is the least–square regression line for this data?

• y = 3.85 – 0.01x
• y = 4.09 – 0.32x
• y = 6.30 – 0.59x
• y = 8.18 – 0.64x

Tags

CCSS.8.EE.C.8C

Which of the following are true about the least–square regression line?
I. The average of its residuals is 0.
II. The sum of its residuals is zero.
III. It is the line that produces the highest r–value.

• III only
• I and II
• I and III
• I, II and III

Tags

CCSS.8.SP.A.2

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

Tags

CCSS.8.EE.C.8C

Victoria found the least squares regression line for a set of data and then graphed a residual plot. She found that all the residuals were above 0. Which of the following is true?

• Every point must have been above the regression line.
• The slope of the regression line must be 0
• The residuals are all outliers
• This is not possible and must be the result of an error on Victoria's part.

Tags

CCSS.HSS.ID.B.6B