Unit 3 Test: Connections Between Data

The scatter plot shows the number of hats and scarves each knitter sold at a knitting show. How many hats did the knitter who sold 9 scarves sell?

• 2

• 3

• 4

• 6

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CCSS.HSF.IF.A.2

Which best describes the association between variables x and y?

• strong positive

• strong negative

• weak positive

• weak negative

Tags

CCSS.HSF-LE.A.1B

For the data shown in the scatter plot, which is the best estimate of r?

• -0.95

• -0.55

• 0.55

• 0.95

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CCSS.HSS.ID.C.8

CCSS.HSS.ID.B.6

In one study, it was found that the correlation coefficient between two variables is -0.32. Which statement is true?

• There is a weak positive association between the variables.

• There is a weak negative association between the variables.

• There is a strong positive association between the variables.

• There is a strong negative association between the variables.

Tags

CCSS.HSS.ID.C.8

Rounded to three decimal places, what is the value of r for this data set?

• 0.870

• 0.897

• 0.978

• 0.989

Tags

CCSS.HSS.ID.C.8

A study of several cities shows a positive correlation between the percent of people late to work and the amount of pollution on the roadways. Which statement is most likely true?

• Pollution makes people late to work.

• People who tend to be late make more pollution than those who tend to be on time.

• The correlation is due to a third variable: traffic.

• The correlation is due to a third variable: cost of windshield wiper fluid.

Tags

CCSS.HSF.LE.B.5

The regression equation

 $y=1.3x+6.8$  approximates the number of minutes it takes an employee to drive to work, y, given the number of miles the employee has to drive, x. 
Which statement is true? 

• For every extra mile an employee drives, the driving time increases by 6.8 minutes.

• For every extra mile an employee drives, the driving time increases by 1.3 minutes.

• For every extra minute an employee drives, the distance increases by 6.8 miles.

• For every extra minute an employee drives, the distance increases by 1.3 miles.

Tags

CCSS.HSF.LE.B.5

The regression equation

 $y=-0.414x+106.55$  approximates the percent of people in an audience who finish watching a documentary, y, given the length of the film in minutes, x. 

Which percent is the best prediction for the percent of people in an audience who will finish watching a documentary that is 70 minutes long?

• 15%

• 29%

• 56%

• 78%

Tags

CCSS.8.EE.C.8C

The correlation coefficient r between an employee's age, x, and yearly salary, y, is 0.633. What percent of the variation in yearly salaries can be explained by differences in the employees' ages?

• 15.8%

• 31.7%

• 40.1%

• 68.3%

Tags

CCSS.HSS.ID.C.8

The regression equation

 $y=3.648\cdot1.182^x$  approximates the cost to go on a safari, y, given the number of years since it opened in 2005, x. Which amount is the best estimate for the cost of a vehicle to drive through the safari in 2009?

• $7.12

• $8.38

• $16.43

• $17.25

Tags

CCSS.HSF.LE.B.5