Unit 2: Exploring Two-Variable Data

What letter do we use to represent correlation coefficient?

• c
• r
• p
• h

Tags

CCSS.8.SP.A.1

CCSS.8.SP.A.2

Describe the correlation in the graph shown.

• Strong Negative
• Strong Positive
• Weak Negative
• Weak Positive

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.7

CCSS.HSS.ID.C.8

What would be the correlation between study time and test grades?

• positive
• negative
• none
• cannot be determined

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

CCSS.HSS.ID.C.9

The linear regression equation is y = 61.93x - 1.79.  Identify the y-intercept of the equation.

• Y-Int = 61.93
• Y-Int = -1.79
• Y-Int = (0, -1.79)
• Y-Int = (0, 61.93)

Tags

CCSS.HSS.ID.C.7

The linear regression equation is y = 61.93x - 1.79.  Identify the slope of the equation.

• Slope = 61.93
• Slope = -1.79
• Slope = (0, -1.79)
• Slope = (0, 61.93)

Tags

CCSS.HSF.LE.B.5

The linear regression equation is y = 61.93x - 1.79.  According to the equation, the y-intercept can be interpreted as:

• After 0 hours of driving, they went -1.79 miles.
• They are driving -1.79 miles per hour.
• They drove 1.79 miles total.
• They drive 1.79 hours total.

Tags

CCSS.HSS.ID.C.7

What type of correlation does this graph show?

• Positive
• negative
• none
• all of the above

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

The residual plots from five different least squares regression lines are shown below. Which of the plots shows the strongest evidence that its regression line is an appropriate model for the data and is consistent with the assumptions required for inference for regression?

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• 
• 
• 
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Tags

CCSS.HSS.ID.A.3

The computer output below shows the result of a linear regression analysis for predicting the concentration of zinc, in parts per million (ppm), from the concentration of lead, in ppm, found in fish from a certain river. Which of the following statements is a correct interpretation of the value 19.0 in the output?

• On average there is a predicted increase of 19.0 ppm in concentration of lead for every increase of 1 ppm in concentration of zinc found in the fish.

• On average there is a predicted increase of 19.0 ppm in concentration of zinc for every increase of 1 ppm in concentration of lead found in the fish.

• The predicted concentration of zinc is 19.0 ppm in fish with no concentration of lead.

• The predicted concentration of lead is 19.0 ppm in fish with no concentration of zinc.

• Approximately 19% of the variability in the zinc concentration is predicted by its linear relationship with lead concentration.

Tags

CCSS.HSF.LE.B.5

The following computer output describes the relationship between y = height (in cm) and x = foot length (also in cm) for 12 randomly selected students from the British Census @ Schools database. The scatterplot for this relationship show a roughly linear shape. Which of the following is an equation of least-squares regression line for these data?

• Height = 117.99 + 1.878 (Foot Length)
• Foot Length = 117.99 + 1.878 (Height)
• Height = 1.878 + 117.99 (Foot Length)
• Foot Length = 1.878 + 117.99 (Height)

Tags

CCSS.HSA.CED.A.2

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.7

CCSS.HSS.ID.C.8