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Unit 5 Day 3 Correlation Practice #2

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Last updated almost 5 years ago
26 questions
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Question 1
1.

Question 2
2.

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.

Question 3
3.

Question 4
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.

Question 5
5.

Question 6
6.

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.

Question 7
7.

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?

Question 8
8.

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.

Question 9
9.

Question 10
10.

Question 11
11.

Question 12
12.

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?

Question 13
13.

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.

Question 14
14.

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 itemarrow_right_altCorresponding Item
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.
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Correlation coefficients cannot be negative.
Question 15
15.

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

Question 16
16.

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?

Question 17
17.

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?

Question 18
18.

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?

Question 19
19.

Use the following graphs to answer the question:

Which plot shows a relationship that is approximately linear?

Question 20
20.

Use the following graphs to answer the question:

Which plots show a relationship that is very strong?

Question 21
21.

Use the following graphs to answer the question:

Which plot shows a relationship that is negative?

Question 22
22.

Use the following graphs to answer the question:

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

Question 23
23.

Use the following graphs to answer the question:

Which plot shows a moderately strong association?

Question 24
24.

Question 25
25.

Question 26
26.

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

Draggable itemarrow_right_altCorresponding Item
a
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0.006
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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
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
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
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.
Correlation can only be found between quantitative variables, he observed an association.
Correlation does not have units, it is an r value only.
The correlation between Olympic Gold Medal times for the 800 m hurdles and year is -0.66 seconds per year.
Correlation values are only from -1.0 to +1.0, they will never be outside that range.
The correlation between Olympic gold medal times for the 100 m dash and year is -1.37.
Changing the x & y axis for the scatterplot does not change the correlation coefficient. The correlation remains the same.

The correlation coefficient does not change if different units are used. It is not affected by scaling or shifting.
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.
D
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.
2 only
2 and 3 only
2 only
1 and 3 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
b
0.777
c
-0.923
d
-0.487

0.936