In the following relationship, is r > 0 or r < 0? Closer to r = 0 or r = ± 1? Explain your reasoning.

Because the relationship is positive, r >0. Also, r is closer to 0 because the relationship is weak.

Because the relationship is positive, r >0. Also, r is closer to 1 because the relationship is strong.

Because the relationship is negative, r < 0. Also, r is closer to 0 because the relationship is weak.

Because the relationship is negative, r <0. Also, r is closer to -1 because the relationship is strong.

In the following relationship, is r > 0 or r < 0? Closer to r = 0 or r = ± 1? Explain your reasoning.

Because the relationship is negative, r < 0. Also, r is closer to 0 because the relationship is weak.

Because the relationship is positive, r >0. Also, r is closer to 0 because the relationship is weak.

Because the relationship is positive, r >0. Also, r is closer to 1 because the relationship is strong.

Because the relationship is negative, r <0. Also, r is closer to -1 because the relationship is strong.

In the following relationship, is r > 0 or r < 0? Closer to r = 0 or r = ± 1? Explain your reasoning.

Because the relationship is negative, r <0. Also, r is closer to -1 because the relationship is strong.

Because the relationship is positive, r >0. Also, r is closer to 0 because the relationship is weak.

Because the relationship is positive, r >0. Also, r is closer to 1 because the relationship is strong.

Because the relationship is negative, r < 0. Also, r is closer to 0 because the relationship is weak.

In the following relationship, is r > 0 or r < 0? Closer to r = 0 or r = ± 1? Explain your reasoning.

Because the relationship is positive, r >0. Also, r is closer to 1 because the relationship is strong.

Because the relationship is positive, r >0. Also, r is closer to 0 because the relationship is weak.

Because the relationship is negative, r < 0. Also, r is closer to 0 because the relationship is weak.

Because the relationship is negative, r <0. Also, r is closer to -1 because the relationship is strong.

There is a linear relationship between the number of turnovers and the number of points scored for players in the 2013–2014 NBA season. The correlation for these data is r = 0.92. Interpret this value.

The correlation of 0.92 indicates that the linear relationship between turnovers and the number of points scored for players in the 2013-2014 NBA season is strong and positive.

The correlation of 0.92 indicates that the nonlinear relationship between turnovers and the number of points scored for players in the 2013-2014 NBA season is strong and negative.

The correlation of 0.92 indicates that the linear relationship between turnovers and the number of points scored for players in the 2013-2014 NBA season is weak and negative.

The correlation of 0.92 indicates that the linear relationship between turnovers and the number of points scored for players in the 2013-2014 NBA season is weak and positive.

Infants who cry easily may be more easily stimulated than others. This may be a sign of higher IQ. Child development researchers explored the relationship between the crying of infants 4 to 10 days old and their IQ test scores at age 3. A snap of a rubber band on the sole of the foot caused the infants to cry. The researchers recorded the crying and measured its intensity by the number of peaks in the most active 20 seconds. The relationship between these variables is linear, with a correlation of r = 0.45. Interpret this value.

The correlation of 0.45 indicates that the linear relationship between the number of crying peaks and IQ test scores at age 3 is moderate and positive.

The correlation of 0.45 indicates that the linear relationship between the number of crying peaks and IQ test scores at age 3 is strong and positive.

The correlation of 0.45 indicates that the nonlinear relationship between the number of crying peaks and IQ test scores at age 3 is strong and negative.

The correlation of 0.45 indicates that the linear relationship between the number of crying peaks and IQ test scores at age 3 is moderate and negative.

There is a linear relationship between the number of turnovers and the number of points scored for players in the 2013–2014 NBA season. The correlation for these data is r = 0.92. Does the fact that r = 0.92 suggest that an increase in turnovers will cause NBA players to score more points? Explain.

Probably not. Although there is a strong, positive correlation, an increase in turnovers is not likely to cause an increase in points for NBA players. It is likely that both of these variables are changing due to several other variables.

Probably. There is a strong, positive correlation, an increase in turnovers is likely to cause an increase in points for NBA players.

Probably. There is a weak, positive correlation, an increase in turnovers is likely to cause an increase in points for NBA players.

Probably not. There is a weak, positive correlation, an increase in turnovers is not likely to cause an increase in points for NBA players. It is likely that both of these variables are changing due to several other variables.

Infants who cry easily may be more easily stimulated than others. This may be a sign of higher IQ. Child development researchers explored the relationship between the crying of infants 4 to 10 days old and their IQ test scores at age 3. A snap of a rubber band on the sole of the foot caused the infants to cry. The researchers recorded the crying and measured its intensity by the number of peaks in the most active 20 seconds. The relationship between these variables is linear, with a correlation of r = 0.45. Does the fact that r = 0.45 suggest that making an infant cry will increase his or her IQ later in life? Explain.

Probably not. Although there is a somewhat weak, positive correlation, an increase in the number of times an infant cries is not likely to cause higher IQ scores later in life. It is likely that both of these variables are changing due to several other variables.

Probably. Although there is a somewhat weak, positive correlation, an increase in the number of times an infant cries is likely to cause higher IQ scores later in life.

Probably not. Although there is a strong, positive correlation, an increase in the number of times an infant cries is not likely to cause higher IQ scores later in life. It is likely that both of these variables are changing due to several other variables.

Probably. Although there is a strong, positive correlation, an increase in the number of times an infant cries is likely to cause higher IQ scores later in life.

Here are the heights in inches and number of rebounds in the 2014 playoffs for 7 members of the NBA champion San Antonio Spurs. Calculate the correlation.

There is no such thing as correlation.

Here are the number of enrolled students (in 1000s) and the number of burglaries for 8 public universities in one U.S. state. Calculate the correlation.

r = 0.80 number of students per number of burglaries

There is no such thing as correlation.

In a famous study published in 1948, communications engineer George Washington Pierce investigated the relationship between air temperature and the rate at which crickets chirp. The scatterplot displays his data on air temperature (in degrees Fahrenheit) and the chirp rate of the striped ground cricket (in chirps per minute). The correlation is r = 0.835. What would happen to the correlation if chirp rate was plotted on the horizontal axis and air temperature was plotted on the vertical axis? Explain.

The correlation would stay the same, r = 0.835, because it doesn't change when the variables switch axes.

The correlation would stay the same, r = 0.835, because it doesn't change when the units switch.

The correlation has no units and would just be r = 0.835.

In a famous study published in 1948, communications engineer George Washington Pierce investigated the relationship between air temperature and the rate at which crickets chirp. The scatterplot displays his data on air temperature (in degrees Fahrenheit) and the chirp rate of the striped ground cricket (in chirps per minute). The correlation is r = 0.835. What would happen to the correlation if air temperature was measured in degrees Celsius instead of degrees Fahrenheit? Explain.

The correlation would stay the same, r = 0.835, because it doesn't change when the units switch.

The correlation would stay the same, r = 0.835, because it doesn't change when the variables switch axes.

The correlation has no units and would just be r = 0.835.

In a famous study published in 1948, communications engineer George Washington Pierce investigated the relationship between air temperature and the rate at which crickets chirp. The scatterplot displays his data on air temperature (in degrees Fahrenheit) and the chirp rate of the striped ground cricket (in chirps per minute). The correlation is r = 0.835. Mariko claims that the correlation between chirp rate and temperature is r = 0.835 chirps per minute per degree Fahrenheit. Is this correct? Explain.

The correlation has no units and would just be r = 0.835.

The correlation would stay the same, r = 0.835, because it doesn't change when the variables switch axes.

The correlation would stay the same, r = 0.835, because it doesn't change when the units switch.

Chapter 6 Checkpoint

Authored by Krysten Martinez

Mathematics

11th - 12th Grade

CCSS covered

Used 5+ times

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25 questions

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MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Identify the response variable for the following relationship.
The amount of time studying for a statistics exam and the grade on the exam.

The amount of time studying for a statistics exam

The grade on the exam

Both could be the response

Both could be the explanatory

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Identify the explanatory variable for the following relationship.
The amount of time studying for a statistics exam and the grade on the exam.

The amount of time studying for a statistics exam

The grade on the exam

Both could be the response

Both could be the explanatory

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Identify the explanatory variable for the following relationship.
The number of texts and the number of calls for cell-phone users.

The number of texts for cell-phone users

Number of calls for cell-phone users

Both could be the response

Both could be the explanatory

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Identify the response variable for the following relationship.
The number of texts and the number of calls for cell-phone users.

The number of texts for cell-phone users

Number of calls for cell-phone users

Both could be the response

Both could be the explanatory

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Many people like to ride roller coasters. Amusement parks try to increase attendance by building exciting new coasters. The table displays data on several roller coasters that were opened in a recent year. Make a scatterplot to show the relationship between height and maximum speed.

What is the explanatory variable?

Height of the roller coaster

Maximum Speed of the roller coaster

Both could be the explanatory

There is no explanatory variable.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Many people like to ride roller coasters. Amusement parks try to increase attendance by building exciting new coasters. The table displays data on several roller coasters that were opened in a recent year. Make a scatterplot to show the relationship between height and maximum speed.

What is the response variable?

Height of the roller coaster

Maximum Speed of the roller coaster

Both could be the explanatory

There is no explanatory variable.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Many people like to ride roller coasters. Amusement parks try to increase attendance by building exciting new coasters. The table displays data on several roller coasters that were opened in a recent year. Make a scatterplot to show the relationship between height and maximum speed.

Which of the following is the scatterplot?

You can't make a scatterplot for categorical variables.

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Chapter 6 Checkpoint

Identify the response variable for the following relationship.The amount of time studying for a statistics exam and the grade on the exam.

Identify the explanatory variable for the following relationship.The amount of time studying for a statistics exam and the grade on the exam.

Identify the explanatory variable for the following relationship.The number of texts and the number of calls for cell-phone users.

Identify the response variable for the following relationship.The number of texts and the number of calls for cell-phone users.

Access all questions and much more by creating a free account

Similar Resources on Wayground

Popular Resources on Wayground

Discover more resources for Mathematics

Identify the response variable for the following relationship.
The amount of time studying for a statistics exam and the grade on the exam.

Identify the explanatory variable for the following relationship.
The amount of time studying for a statistics exam and the grade on the exam.

Identify the explanatory variable for the following relationship.
The number of texts and the number of calls for cell-phone users.

Identify the response variable for the following relationship.
The number of texts and the number of calls for cell-phone users.