Unit 5 Day 3 Correlation Practice #2

Last updated almost 5 years ago

26 questions

4

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Unit 5 Day 3 Correlation Practice #2

Last updated almost 5 years ago

26 questions

4

Data was collected by an insurance company on the speed driven and accidents reported. Use the table below to analyze the possible relationship between speed and # of accidents.

Use the information above (entered in L1 & L2)
Calculate the correlation coefficient (r).
Stat, Calc, #8 LinReg(a+bx)
Round your answer to three places past the decimal.

4

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.

Using the scatterplot created in #5, is it appropriate to calculate the correlation coefficient?

4

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.

Calculate the correlation coefficient.
Stat, Calc, #8 LinReg(a+bx).
Enter the correlation coefficent, round to three places past the decimal if needed.

4

Draggable item		Corresponding Item

4

A survey of the world's nations in 2004 showed a strong positive correlation between percentage of the country using cell phones and life expectancy in year at birth.
Does this mean cell phones are good for your health?

4

A survey of the world's nations in 2004 showed a strong positive correlation between percentage of the country using cell phones and life expectancy in year at birth.
What might explain the strong correlation?
What might be the lurking variable?

4

Draggable item		Corresponding Item

Data was collected by an insurance company on the speed driven and accidents reported. Use the table below to analyze the possible relationship between speed and # of accidents.

Clear List 1 and List 2, enter the data into L1 & L2.
Create a scatterplot using Statplot #1, ZoomStat (9).
Describe the relationship between speed and average # of accidents.
Select all that apply.

Data was collected by an insurance company on the speed driven and accidents reported. Use the table below to analyze the possible relationship between speed and # of accidents.

Use the scatterplot from #15, interpret the relationship between speed and average # of accidents.

There is no relationship between speed and the number of accidents.

As speed increases, the number of accidents strongly decreases.

As speed increases, the number of accidents strongly increases.

As speed increases, the number of accidents slightly decreases.

As speed increases, the number of accidents slightly increases.

Data was collected by an insurance company on the speed driven and accidents reported. Use the table below to analyze the possible relationship between speed and # of accidents.

Use the scatterplot from #15:
1. What are the three conditions that need to be met to calculate the correlation coefficient (r)?
2. is it appropriate to calculate the correlation coefficient?
Select all four answers:

Data was collected by an insurance company on the speed driven and accidents reported. Use the table below to analyze the possible relationship between speed and # of accidents.

Use the information above (entered in L1 & L2)
Calculate the correlation coefficient (r).
Stat, Calc, #8 LinReg(a+bx)
Round your answer to three places past the decimal.

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.

Enter the data into your Ti-84, Stat, Edit.
To enter the year, use the number of years since 1900.
Ex. 1920=20, the year 2012= 112
Make sure you remember in which lists you enter the data, it's your choice.

Create a scatterplot of the data to show the relationship between year and time.
Describe the relationship between year and time for the men's 1500m run.

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.

Use the scatterplot created in #5.
Interpret the relationship between year and time for the men's 1500m run.

As the years increase the 1500 meter run time increases.

As the years increase the 1500 meter run time decreases.

As the years increase the 1500 meter run time does not appear to change.

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.

Using the scatterplot created in #5, is it appropriate to calculate the correlation coefficient?

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.

Calculate the correlation coefficient.
Stat, Calc, #8 LinReg(a+bx).
Enter the correlation coefficent, round to three places past the decimal if needed.

Another group of 10 adults were studied, their heights and weights were recorded in the table below.

Enter the data into lists in your calculator. Make sure you remember/know which lists they are in.
Create a scatterplot using Ht. as the Xlist and weight as the Ylist.
Describe the relationship between height and weight for this group of adults.

Another group of 10 adults were studied, their heights and weights were recorded in the table below.

Using the scatterplot created in #9, is it appropriate to calculate the correlation coefficient?
Why or why not

If a group of data has a correlation coefficient of -0.875, what does this tell you about the description of the scatterplot?
It will be...

If a group of data comparing grades and hours studied has a correlation coefficient of 0.452, what does this tell your about the relationship?

As hours studied increases, the grades increase moderately.

As hours studied increases, the grades don't change much.

As hours studied increases, the grades increase strongly.

As hourse studied increases, the grades decrease slightly.

As hours studied increases, the grades decrease strongly.

Your friend conducts a study and reports: 'I have found a strong correlation between eye color and gender'.
Is this statement true or false?
Explain why.
Select both correct answers.

He did a study, evaluated his data and observed a correlation based on his scatterplot.

False

Correlation can only be found between quantitative variables, he observed an association.

True

Identify what is wrong with each of the following statements.
Match each statement to the reason why it is incorrect.
There will be one left over reason.

Draggable item		Corresponding Item
Since the correlation between Olympic gold medal times for the 800 m hurdles and 100 m dash is -0.41, the correlation between 100 m dash times and the 800 m hurdles is +0.41.		Correlation does not have units, it is an r value only.
If we were to measure Olympic gold medal times for the 800 m hurdles in minutes instead of seconds the correlation would be -0.66/60 = -0.011.		Correlation values are only from -1.0 to +1.0, they will never be outside that range.
		Changing the x & y axis for the scatterplot does not change the correlation coefficient. The correlation remains the same.
The correlation between Olympic Gold Medal times for the 800 m hurdles and year is -0.66 seconds per year.		The correlation coefficient does not change if different units are used. It is not affected by scaling or shifting.
The correlation between Olympic gold medal times for the 100 m dash and year is -1.37.		Correlation coefficients cannot be negative.

Select the scatterplot that shows a STRONG relationship between x and y,
yet has a correlation coefficient of r=0.
A. B. C. D.

A

B

C

D

A study by a prominent psychologist found a moderately strong positive association between the number of hours of sleep a person gets and the person's ability to memorize information.
What does this positive association mean?

An increase in the number of hours of sleep causes a decreased ability to memorize information.

An increase in the number of hours of sleep is associated with a decreased ability to memorize information.

An increase in the number of hours of sleep is associated with an increased ability to memorize information.

An increase in the number of hours of sleep a person gets causes them be able to memorize information better.

There could be a lurking variable, not measured, that is related to both the number of hours of sleep and the ability to memorize information.

A survey of the world's nations in 2004 showed a strong positive correlation between percentage of the country using cell phones and life expectancy in year at birth.
Does this mean cell phones are good for your health?

A survey of the world's nations in 2004 showed a strong positive correlation between percentage of the country using cell phones and life expectancy in year at birth.
What might explain the strong correlation?
What might be the lurking variable?

Use the following graphs to answer the question:

Which plot shows a relationship that is approximately linear?

2 and 4 only

1 only

2, 3 and 4

2 only

Use the following graphs to answer the question:

Which plots show a relationship that is very strong?

3 only

1 and 4 only

2 only

2 and 3 only

Use the following graphs to answer the question:

Which plot shows a relationship that is negative?

2 and 3 only

1 and 4 only

3 only

2 only

Use the following graphs to answer the question:

Which plot shows a relationship that has a correlation near zero?

2 only

1 only

2 and 3 only

1 and 3 only

Use the following graphs to answer the question:

Which plot shows a moderately strong association?

1 only

2 and 3 only

4 only

1 and 4 only

Suppose you were to collect data for the variables altitude and temperature when climbing mountains.
Which would be the explanatory variable?
Which would be the response variable?
What form, direction and strength do you think you would observe?

Response = altitude

Positive, strong, possibly linear

Positive, weak to moderate, possibly linear

Negative, strong, possibly linear

Negative, weak to moderate, possibly linear

Explanatory = altitude

Explanatory = temperature

Response = temperature

Suppose you were to collect data for the variables distance and time delay when predicting how far away a lightening strike occurred.
Which would be the explanatory variable?
Which would be the response variable?
What form, direction and strength do you think you would observe?

Use the following four graphs, match each graph to the corresponding correlation coefficient (r).

Draggable item		Corresponding Item
b		0.006
d		0.777
		-0.923
c		-0.487
a		0.936

Data was collected by an insurance company on the speed driven and accidents reported. Use the table below to analyze the possible relationship between speed and # of accidents.

Clear List 1 and List 2, enter the data into L1 & L2.
Create a scatterplot using Statplot #1, ZoomStat (9).
Describe the relationship between speed and average # of accidents.
Select all that apply.

Weak

Moderate

Scattered

Negative

Positive

Strong

Curved

Linear

No direction

Data was collected by an insurance company on the speed driven and accidents reported. Use the table below to analyze the possible relationship between speed and # of accidents.

Use the scatterplot from #15, interpret the relationship between speed and average # of accidents.

There is no relationship between speed and the number of accidents.

As speed increases, the number of accidents strongly decreases.

As speed increases, the number of accidents strongly increases.

As speed increases, the number of accidents slightly decreases.

As speed increases, the number of accidents slightly increases.

Data was collected by an insurance company on the speed driven and accidents reported. Use the table below to analyze the possible relationship between speed and # of accidents.


Use the scatterplot from #15:
1. What are the three conditions that need to be met to calculate the correlation coefficient (r)?
2. is it appropriate to calculate the correlation coefficient?
Select all four answers:

Straight Enough (Nearly Linear) Condition

Yes

No

Quantitative Data Condition

Nearly Normal Condition

Categorical Data Condition

Outlier Condition

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.

Enter the data into your Ti-84, Stat, Edit. 
To enter the year, use the number of years since 1900. 
Ex. 1920=20,  the year 2012= 112
Make sure you remember in which lists you enter the data, it's your choice.

Create a scatterplot of the data to show the relationship between year and time.
Describe the relationship between year and time for the men's 1500m run.   

No direction

Negative

Weak

Positve

Linear

Strong

Moderate

Curved

Scattered

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.


Use the scatterplot created in #5.
Interpret the relationship between year and time for the men's 1500m run.

As the years increase the 1500 meter run time increases.

As the years increase the 1500 meter run time decreases.

As the years increase the 1500 meter run time does not appear to change.

Another group of 10 adults were studied, their heights and weights were recorded in the table below.

Enter the data into lists in your calculator. Make sure you remember/know which lists they are in.
Create a scatterplot using Ht. as the Xlist and weight as the Ylist.
Describe the relationship between height and weight for this group of adults.

Weak 

Positive

Strong

No direction

Scattered

Moderate

Curved

Negative

Linear

Another group of 10 adults were studied, their heights and weights were recorded in the table below.

Using the scatterplot created in #9, is it appropriate to calculate the correlation coefficient?
Why or why not

It meets all three conditions.

It does not meet the Quantitative Data Condition.

It does not meet the Outlier Condition.

Yes

No

It does not meet the Straight Enough Condition.

If a group of data has a correlation coefficient of -0.875, what does this tell you about the description of the scatterplot?
It will be...

Possibly Linear

Positive

Scattered

Weak

No direction

Negative

Curved

Moderate

Strong

If a group of data comparing grades and hours studied has a correlation coefficient of 0.452, what does this tell your about the relationship?

As hours studied increases, the grades increase moderately.

As hours studied increases, the grades don't change much.

As hours studied increases, the grades increase strongly.

As hourse studied increases, the grades decrease slightly.

As hours studied increases, the grades decrease strongly.

Your friend conducts a study and reports: 'I have found a strong correlation between eye color and gender'.
Is this statement true or false?
Explain why.
Select both correct answers.

He did a study, evaluated his data and observed a correlation based on his scatterplot.

False

Correlation can only be found between quantitative variables, he observed an association.

True

Identify what is wrong with each of the following statements.
Match each statement to the reason why it is incorrect.
There will be one left over reason.

Since the correlation between Olympic gold medal times for the 800 m hurdles and 100 m dash is -0.41, the correlation between 100 m dash times and the 800 m hurdles is +0.41.

Correlation does not have units, it is an r value only.

If we were to measure Olympic gold medal times for the 800 m hurdles in minutes instead of seconds the correlation would be -0.66/60 = -0.011.

Correlation values are only from -1.0 to +1.0, they will never be outside that range.

Changing the x & y axis for the scatterplot does not change the correlation coefficient. The correlation remains the same.

The correlation between Olympic Gold Medal times for the 800 m hurdles and year is -0.66 seconds per year.

The correlation coefficient does not change if different units are used. It is not affected by scaling or shifting.

The correlation  between Olympic gold medal times for the 100 m dash and year is -1.37.

Correlation coefficients cannot be negative.

Select the scatterplot that shows a STRONG relationship between x and y, 
yet has a correlation coefficient of r=0.
     A.                  B.                 C.                D.   

A

B

C

D

A study by a prominent psychologist found a moderately strong positive association between the number of hours of sleep a person gets and the person's ability to memorize information.
What does this positive association mean?

An increase in the number of hours of sleep causes a decreased ability to memorize information.

An increase in the number of hours of sleep is associated with a decreased ability to memorize information.

An increase in the number of hours of sleep is associated with an increased ability to memorize information.

An increase in the number of hours of sleep a person gets causes them be able to memorize information better.

There could be a lurking variable, not measured, that is related to both the number of hours of sleep and the ability to memorize information.

Use the following graphs to answer the question:

Which plot shows a relationship that is approximately linear?

2 and 4 only

1 only

2, 3 and 4

2 only

Use the following graphs to answer the question:

Which plots show a relationship that is very strong?

3 only

1 and 4 only

2 only

2 and 3 only

Use the following graphs to answer the question:

Which plot shows a relationship that is negative?

2 and 3 only

1 and 4 only

3 only

2 only

Use the following graphs to answer the question:

Which plot shows a relationship that has a correlation near zero?

2 only

1 only

2 and 3 only

1 and 3 only

Use the following graphs to answer the question:

Which plot shows a moderately strong association?

1 only

2 and 3 only

4 only

1 and 4 only

Suppose you were to collect data for the variables altitude and temperature when climbing mountains.
Which would be the explanatory variable?
Which would be the response variable?
What form, direction and strength do you think you would observe?

Response = altitude

Positive, strong, possibly linear

Positive, weak to moderate, possibly linear

Negative, strong, possibly linear

Negative, weak to moderate, possibly linear

Explanatory = altitude

Explanatory = temperature

Response = temperature

Suppose you were to collect data for the variables distance and time delay when predicting how far away a lightening strike occurred.
Which would be the explanatory variable?
Which would be the response variable?
What form, direction and strength do you think you would observe?

Explanatory = distance

Positive, strong, linear

Response = distance

Explanatory = time delay

Negative, strong, linear

Positive, weak to moderate, possibly linear

Negative, weak to moderate, possibly linear

Response = time delay

Use the following four graphs,  match each graph to the corresponding correlation coefficient (r).

b

0.006

d

0.777

-0.923

c

-0.487

a

0.936

Unit 5 Day 3 Correlation Practice #2

Unit 5 Day 3 Correlation Practice #2

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.Using the scatterplot created in #5, is it appropriate to calculate the correlation coefficient?

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.Calculate the correlation coefficient. Stat, Calc, #8 LinReg(a+bx).Enter the correlation coefficent, round to three places past the decimal if needed.

A survey of the world's nations in 2004 showed a strong positive correlation between percentage of the country using cell phones and life expectancy in year at birth.Does this mean cell phones are good for your health?

A survey of the world's nations in 2004 showed a strong positive correlation between percentage of the country using cell phones and life expectancy in year at birth.What might explain the strong correlation?What might be the lurking variable?

Data was collected by an insurance company on the speed driven and accidents reported. Use the table below to analyze the possible relationship between speed and # of accidents.Use the scatterplot from #15, interpret the relationship between speed and average # of accidents.

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.Use the scatterplot created in #5.Interpret the relationship between year and time for the men's 1500m run.

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.Using the scatterplot created in #5, is it appropriate to calculate the correlation coefficient?

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.Calculate the correlation coefficient. Stat, Calc, #8 LinReg(a+bx).Enter the correlation coefficent, round to three places past the decimal if needed.

Another group of 10 adults were studied, their heights and weights were recorded in the table below.Using the scatterplot created in #9, is it appropriate to calculate the correlation coefficient?Why or why not

If a group of data has a correlation coefficient of -0.875, what does this tell you about the description of the scatterplot?It will be...

If a group of data comparing grades and hours studied has a correlation coefficient of 0.452, what does this tell your about the relationship?

Your friend conducts a study and reports: 'I have found a strong correlation between eye color and gender'.Is this statement true or false?Explain why.Select both correct answers.

Identify what is wrong with each of the following statements.Match each statement to the reason why it is incorrect.There will be one left over reason.

Select the scatterplot that shows a STRONG relationship between x and y, yet has a correlation coefficient of r=0. A. B. C. D.

A study by a prominent psychologist found a moderately strong positive association between the number of hours of sleep a person gets and the person's ability to memorize information.What does this positive association mean?

A survey of the world's nations in 2004 showed a strong positive correlation between percentage of the country using cell phones and life expectancy in year at birth.Does this mean cell phones are good for your health?

A survey of the world's nations in 2004 showed a strong positive correlation between percentage of the country using cell phones and life expectancy in year at birth.What might explain the strong correlation?What might be the lurking variable?

Use the following graphs to answer the question:Which plot shows a relationship that is approximately linear?

Use the following graphs to answer the question:Which plots show a relationship that is very strong?

Use the following graphs to answer the question:Which plot shows a relationship that is negative?

Use the following graphs to answer the question:Which plot shows a relationship that has a correlation near zero?

Use the following graphs to answer the question:Which plot shows a moderately strong association?

Suppose you were to collect data for the variables altitude and temperature when climbing mountains.Which would be the explanatory variable?Which would be the response variable?What form, direction and strength do you think you would observe?

Suppose you were to collect data for the variables distance and time delay when predicting how far away a lightening strike occurred.Which would be the explanatory variable?Which would be the response variable?What form, direction and strength do you think you would observe?

Use the following four graphs, match each graph to the corresponding correlation coefficient (r).

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.

Using the scatterplot created in #5, is it appropriate to calculate the correlation coefficient?

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.

Calculate the correlation coefficient.
Stat, Calc, #8 LinReg(a+bx).
Enter the correlation coefficent, round to three places past the decimal if needed.

A survey of the world's nations in 2004 showed a strong positive correlation between percentage of the country using cell phones and life expectancy in year at birth.
Does this mean cell phones are good for your health?

A survey of the world's nations in 2004 showed a strong positive correlation between percentage of the country using cell phones and life expectancy in year at birth.
What might explain the strong correlation?
What might be the lurking variable?

Data was collected by an insurance company on the speed driven and accidents reported. Use the table below to analyze the possible relationship between speed and # of accidents.

Use the scatterplot from #15, interpret the relationship between speed and average # of accidents.

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.

Use the scatterplot created in #5.
Interpret the relationship between year and time for the men's 1500m run.

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.

Using the scatterplot created in #5, is it appropriate to calculate the correlation coefficient?

Men's 1500 meter run Olympic Gold Medal times were recorded for comparison in the table below.

Calculate the correlation coefficient.
Stat, Calc, #8 LinReg(a+bx).
Enter the correlation coefficent, round to three places past the decimal if needed.

Another group of 10 adults were studied, their heights and weights were recorded in the table below.

Using the scatterplot created in #9, is it appropriate to calculate the correlation coefficient?
Why or why not

If a group of data has a correlation coefficient of -0.875, what does this tell you about the description of the scatterplot?
It will be...

Your friend conducts a study and reports: 'I have found a strong correlation between eye color and gender'.
Is this statement true or false?
Explain why.
Select both correct answers.

Identify what is wrong with each of the following statements.
Match each statement to the reason why it is incorrect.
There will be one left over reason.

Select the scatterplot that shows a STRONG relationship between x and y,
yet has a correlation coefficient of r=0.
A. B. C. D.

A study by a prominent psychologist found a moderately strong positive association between the number of hours of sleep a person gets and the person's ability to memorize information.
What does this positive association mean?

A survey of the world's nations in 2004 showed a strong positive correlation between percentage of the country using cell phones and life expectancy in year at birth.
Does this mean cell phones are good for your health?

A survey of the world's nations in 2004 showed a strong positive correlation between percentage of the country using cell phones and life expectancy in year at birth.
What might explain the strong correlation?
What might be the lurking variable?

Use the following graphs to answer the question:

Which plot shows a relationship that is approximately linear?

Use the following graphs to answer the question:

Which plots show a relationship that is very strong?

Use the following graphs to answer the question:

Which plot shows a relationship that is negative?

Use the following graphs to answer the question:

Which plot shows a relationship that has a correlation near zero?

Use the following graphs to answer the question:

Which plot shows a moderately strong association?

Suppose you were to collect data for the variables altitude and temperature when climbing mountains.
Which would be the explanatory variable?
Which would be the response variable?
What form, direction and strength do you think you would observe?

Suppose you were to collect data for the variables distance and time delay when predicting how far away a lightening strike occurred.
Which would be the explanatory variable?
Which would be the response variable?
What form, direction and strength do you think you would observe?