Regressions and Correlations

Which of the following best describes this correlation?

• Positive, Strong

• Negative Strong

• Positive Weak

• Negative Weak

Tags

CCSS.HSF-LE.A.1B

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.HSF.LE.B.5

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

Which of the following is the formula for a regression.

• y = mx + b

• r²

• Observation - Prediction

• m = (r x S_y) / S_x

Which of the following variables is used to represent the correlation?

• C

• n

• S_x

• r

Tags

CCSS.HSS.ID.C.8

What is the direction of the scatter plot?

• Positive Association

• Negative Association

• None

• Linear

Tags

CCSS.HSF-LE.A.1B

Which of the following is the formula for finding the residual?

• predicted y- observed y

• observed y- predicted x

• predicted x - observed x

• observed y - predicted y

Tags

CCSS.HSF-LE.A.1C

A line of regression has the formula:

y = 2.5x + 5.

Find the residual of the point (4 , 8).

• 7

• -7

• 17

• -17

The residual for a point is found to be 1.38. Is this an under-prediction, or over-prediction?

• Over-prediction

• Under-prediction

• Neither

• Impossible to Solve