Regressions and Correlations

Which of the following best describes this correlation?

• Positive, Strong

• Negative Strong

• Positive Weak

• Negative Weak

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

The linear regression equation is y = 61.93x - 1.79. Use the equation to predict how far this person will travel after 10 hours of driving.

• 100

• 730.15

• 617.5

• 500

The linear regression equation is

y = 61.93x - 1.79. According to the model, the slope can be interpreted as:

• After 0 hours of driving, they went 61.93 miles.

• They drove at a speed of 61.93 miles per hour.

• They drove 61.93 miles total.

• They drove 61.93 hours total.

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Tags

CCSS.HSS.ID.C.7

Approximate the correlation of the scatter plot.

• r = 0

• r = 0.4

• r = -0.4

• r = 0.7

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

True or False: The least-squares regression line will always pass throught the ordered-pair (mean of x, mean of y).

• True

• False

Tags

CCSS.HSS.ID.C.7

True or False: The correlation coefficient (r) is only used for linear regressions.

• True

• False

True or False: If the slope of the least square line is positive then the value or r will also be positive.

• True

• False

Describe the correlation in the graph shown.

• A) Strong Negative

• B) Strong Positive

• C) Weak Negative

• D) No Correlation

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

What type of correlation (association)?

The outside temperature and the amount of layers you wear.

• A) Positive correlation

• B) Negative correlation

• D) No correlation

Tags

CCSS.HSF-LE.A.1B

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