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You will now determine if the samples you are working with are independent, or both independent and repeated at the same time.
Your options will be:
Your options will be:
Independent Samples
Both Repeated & Independent Samples
What is a sample?
A sample is list of numeric values produced by a group of individuals or from observations that have some common characteristic.
What does this mean?
Let’s look at an example:
You have been asked to determine if ACT scores from Texas students are similar to national student ACT scores.
You have been asked to determine if ACT scores from Texas students are similar to national student ACT scores. You select a sample of 100 student ACT scores from Texas and determine if they are statistically similar to national ACT scores.
Let’s go back to our definition of a sample:
A sample is list of numeric values produced by a group of individuals or from observations that have some common characteristic.
Here is the problem again:
You have been asked to determine if ACT scores from Texas students are similar to national student ACT scores. You select a sample of 100 student ACT scores from Texas and determine if they are statistically similar to national ACT scores.
Here is the problem again:
Here is the problem again:
What are the numeric values in this problem?
You have been asked to determine if ACT scores from Texas students are similar to national student ACT scores. You select a sample of 100 student ACT scores from Texas and determine if they are statistically similar to national ACT scores.
Here is the problem again:
What are the numeric values in this problem?
ACT scores
You have been asked to determine if ACT scores from Texas students are similar to national student ACT scores. You select a sample of 100 student ACT scores from Texas and determine if they are statistically similar to national ACT scores.
Here is the problem again:
What group produced these scores?
You have been asked to determine if ACT scores from Texas students are similar to national student ACT scores. You select a sample of 100 student ACT scores from Texas and determine if they are statistically similar to national ACT scores.
Here is the problem again:
What group produced these scores?
You have been asked to determine if ACT scores from Texas students are similar to national student ACT scores. You select a sample of 100 student ACT scores from Texas and determine if they are statistically similar to national ACT scores.
Texas Students
Here is the problem again:
What is the basis for group membership?
You have been asked to determine if ACT scores from Texas students are similar to national student ACT scores. You select a sample of 100 student ACT scores from Texas and determine if they are statistically similar to national ACT scores.
Here is the problem again:
What is the basis for group membership?
You have been asked to determine if ACT scores from Texas students are similar to national student ACT scores. You select a sample of 100 student ACT scores from Texas and determine if they are statistically similar to national ACT scores.
Being a student from Texas who took the ACT
Here is what that sample might look like:
Here is what that sample might look like:
100 Texas Student ACT
Scores
Here is what that sample might look like:
100 Texas Student ACT
ScoresData Set
Here is what that sample might look like:
100 Texas Student ACT
Scores
Texas Students
ACT Scores
1 25
2 16
3 28
4 31
5 14
. . .
. . .
100 32
Data Set
100 Texas Student ACT
Scores
Texas Students
ACT Scores
1 25
2 16
3 28
4 31
5 14
. . .
. . .
100 32
Data Set
Back to the definition:
100 Texas Student ACT
Scores
Texas Students
ACT Scores
1 25
2 16
3 28
4 31
5 14
. . .
. . .
100 32
Data Set
A sample is list of numeric values produced by a group of individuals or from observations that have some common characteristic.
100 Texas Student ACT
Scores
Texas Students
ACT Scores
1 25
2 16
3 28
4 31
5 14
. . .
. . .
100 32
Data Set
A sample is list of numeric values produced by a group of individuals or from observations that have some common characteristic.
100 Texas Student ACT
Scores
Texas Students
ACT Scores
1 25
2 16
3 28
4 31
5 14
. . .
. . .
100 32
Data Set
A sample is list of numeric values produced by a group of individuals or from observations that have some common characteristic.
100 Texas Student ACT
Scores
Texas Students
ACT Scores
1 25
2 16
3 28
4 31
5 14
. . .
. . .
100 32
Data Set
A sample is list of numeric values produced by a group of individuals or from observations that have some common characteristic.
100 Texas Student ACT
Scores
Texas Students
ACT Scores
1 25
2 16
3 28
4 31
5 14
. . .
. . .
100 32
Data Set
A sample is list of numeric values produced by a group of individuals or from observations that have some common characteristic.
100 Texas Student ACT
Scores
Texas Students
ACT Scores
1 25
2 16
3 28
4 31
5 14
. . .
. . .
100 32
Data Set
A sample is list of numeric values produced by a group of individuals or from observations that have some common characteristic.
Now that you’ve been introduced to what sample is
Now that you’ve been introduced to what sample is
. . . What are Independent Samples?
A sample is independent from another sample when the subjects or observations in one sample have NO RELATIONSHIP with the subjects or observations in another sample.
For example:
Imagine you have been asked to compare ACT scores between Texas and California students.
What makes these samples independent is that these Texas Students ARE NOT
these California Students
What makes these samples independent is that these Texas Students ARE NOT
these California Students
100 Texas Student ACT
Scores
What makes these samples independent is that these Texas Students ARE NOT
these California Students
100 Texas Student ACT
Scores
What makes these samples independent is that these Texas Students ARE NOT
these California Students
100 Texas Student ACT
Scores
100 California Student ACT
Scores
This may seem very obvious that one groups individuals are not the other groups individuals.
This may seem very obvious that one groups individuals are not the other groups individuals. But, it is an important aspect that makes independent samples – independent!
Consider the following example:
An investigator thinks that people under the age of forty have vocabularies that are different than those of people over sixty years of age. The investigator administers a vocabulary test to a group of 40 younger subjects and to a group of 45 older subjects. Higher scores reflect better performance. The mean score for younger subjects was 14.0 and the mean score for older subjects was 20.0.
An investigator thinks that people under the age of forty have vocabularies that are different than those of people over sixty years of age. The investigator administers a vocabulary test to a group of 40 younger subjects and to a group of 45 older subjects. Higher scores reflect better performance. The mean score for younger subjects was 14.0 and the mean score for older subjects was 20.0.
An investigator thinks that people under the age of forty have vocabularies that are different than those of people over sixty years of age. The investigator administers a vocabulary test to a group of 40 younger subjects and to a group of 45 older subjects. Higher scores reflect better performance. The mean score for younger subjects was 14.0 and the mean score for older subjects was 20.0.
An investigator thinks that people under the age of forty have vocabularies that are different than those of people over sixty years of age. The investigator administers a vocabulary test to a group of 40 younger subjects and to a group of 45 older subjects. Higher scores reflect better performance. The mean score for younger subjects was 14.0 and the mean score for older subjects was 20.0.
How many samples are there?
An investigator thinks that people under the age of forty have vocabularies that are different than those of people over sixty years of age. The investigator administers a vocabulary test to a group of 40 younger subjects and to a group of 45 older subjects. Higher scores reflect better performance. The mean score for younger subjects was 14.0 and the mean score for older subjects was 20.0.
How many samples are there?
Sample 1
An investigator thinks that people under the age of forty have vocabularies that are different than those of people over sixty years of age. The investigator administers a vocabulary test to a group of 40 younger subjects and to a group of 45 older subjects. Higher scores reflect better performance. The mean score for younger subjects was 14.0 and the mean score for older subjects was 20.0.
How many samples are there?
Sample 2
An investigator thinks that people under the age of forty have vocabularies that are different than those of people over sixty years of age. The investigator administers a vocabulary test to a group of 40 younger subjects and to a group of 45 older subjects. Higher scores reflect better performance. The mean score for younger subjects was 14.0 and the mean score for older subjects was 20.0.
Are they independent?
Yes, they are independent!
Because none of the younger subjects can be in the older sample and none of the older subjects can be in the younger
sample.
Next:
What are repeated samples?
With repeated samples the two samples share one important thing in common:
With repeated samples the two samples share one important thing in common: They are the SAME PERSONS being measured . . .
With repeated samples the two samples share one important thing in common: They are the SAME PERSONS being measured more than once . . .
With repeated samples the two samples share one important thing in common: They are the SAME PERSONS being measured more than once or they are different persons but MATCHED in some way.
Consider this example:
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep.
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours.
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again.
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
You will notice that there is only one group we are studying
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
You will notice that there is only one group we are studying
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Subjects
Subject 1
Subject 2
. . .
Subject 45
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Subjects
Subject 1
Subject 2
. . .
Subject 45
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Before the Study
Subjects
Subject 1
Subject 2
. . .
Subject 45
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Before the Study
Subjects Hours of Sleep
Subject 1 5
Subject 2 4
. . .
Subject 45 7
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Before the Study
Subjects Hours of Sleep
Subject 1 5
Subject 2 4
. . .
Subject 45 7
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Before the Study
Subjects Hours of Sleep
Subject 1 5
Subject 2 4
. . .
Subject 45 7
One Month Later
Hours of Sleep
6
5
8
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Before the Study
Subjects Hours of Sleep
Subject 1 5
Subject 2 4
. . .
Subject 45 7
One Month Later
Hours of Sleep
6
5
8
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Hours of Sleep658
Before the Study
Subjects Hours of Sleep
Subject 1 5
Subject 2 4
. . .
Subject 45 7
One Month Later
Hours of Sleep
6
5
8
Hours of Sleep
7
6
8
Two Months Later
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Hours of Sleep658
Before the Study
Subjects Hours of Sleep
Subject 1 5
Subject 2 4
. . .
Subject 45 7
One Month Later
Hours of Sleep
6
5
8
Hours of Sleep
7
6
8
Two Months Later
Notice that the research subjects are the same, but the samples are taken
at different times.
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Hours of Sleep658
Before the Study
Subjects Hours of Sleep
Subject 1 5
Subject 2 4
. . .
Subject 45 7
One Month Later
Hours of Sleep
6
5
8
Hours of Sleep
7
6
8
Two Months Later
Notice that the research subjects are the same, but the samples are taken
at different times.
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Hours of Sleep658
Before the Study
Subjects Hours of Sleep
Subject 1 5
Subject 2 4
. . .
Subject 45 7
One Month Later
Hours of Sleep
6
5
8
Hours of Sleep
7
6
8
Two Months Later
Notice that the research subjects are the same, but the samples are taken
at different times.
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Hours of Sleep658
Before the Study
Subjects Hours of Sleep
Subject 1 5
Subject 2 4
. . .
Subject 45 7
One Month Later
Hours of Sleep
6
5
8
Hours of Sleep
7
6
8
Two Months Later
Notice that the research subjects are the same, but the samples are taken
at different times.
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Hours of Sleep658
Before the Study
Subjects Hours of Sleep
Subject 1 5
Subject 2 4
. . .
Subject 45 7
One Month Later
Hours of Sleep
6
5
8
Hours of Sleep
7
6
8
Two Months Later
Notice that the research subjects are the same, but the samples are taken
at different times.
Suppose that, as a health researcher, you want to examine the impact of a specialized dietary regimen on hours of sleep. Before they start the regimen, you measure 45 subject’s average sleep hours. One month later you take their average number of sleep hours again. And then two months after that you take the measure one more time.
Hours of Sleep658
Before the Study
Subjects Hours of Sleep
Subject 1 5
Subject 2 4
. . .
Subject 45 7
One Month Later
Hours of Sleep
6
5
8
Hours of Sleep
7
6
8
Two Months Later
Notice that the research subjects are the same, but the samples are taken
at different times.
These samples are repeated because in this case each sample has the same person in it being measured repeatedly.
In some instances, the persons are not the same but are matched on some variable.
In some instances, the persons are not the same but are matched on some variable.
In such a scenario, the samples would be considered to be repeated.
Consider the next example:
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
First, notice that there are multiple measurements over time.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
First, notice that there are multiple measurements over time.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
First, notice that there are multiple measurements over time.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
First, notice that there are multiple measurements over time.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
Next notice that Bob, Tanner, and Mckay are all matched on four variables.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
Next notice that Bob, Tanner, and Mckay are all matched on four variables.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
Next notice that Bob, Tanner, and Mckay are all matched on four variables.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
Next notice that Bob, Tanner, and Mckay are all matched on four variables.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
Next notice that Bob, Tanner, and Mckay are all matched on four variables.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
Next notice that Bob, Tanner, and Mckay are all matched on four variables.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
Next notice that Bob, Tanner, and Mckay are all matched on four variables.
1- Gender
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
Next notice that Bob, Tanner, and Mckay are all matched on four variables.
2- Residence
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
Next notice that Bob, Tanner, and Mckay are all matched on four variables.
3 - Age
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 7
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
Next notice that Bob, Tanner, and Mckay are all matched on four variables.
4- Heart Condition
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
So, Bob, Tanner, and Mckay are not the same person but they are matched in terms of gender,
residence, age and heart condition.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
So, Bob, Tanner, and Mckay are not the same person but they are matched in terms of gender,
residence, age and heart condition.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
So, Bob, Tanner, and Mckay are not the same person but they are matched in terms of gender,
residence, age and heart condition.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
So, Bob, Tanner, and Mckay are not the same person but they are matched in terms of gender,
residence, age and heart condition.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
So, Bob, Tanner, and Mckay are not the same person but they are matched in terms of gender,
residence, age and heart condition.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
So, Bob, Tanner, and Mckay are not the same person but they are matched in terms of gender,
residence, age and heart condition.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
So, Bob, Tanner, and Mckay are not the same person but they are matched in terms of gender,
residence, age and heart condition.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
So, Bob, Tanner, and Mckay are not the same person but they are matched in terms of gender,
residence, age and heart condition.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
The same is true for Ashton, Roger, and Stevewho are not the same person but who are also
matched in terms of gender, residence, age and heart condition.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
The same is true for Ashton, Roger, and Stevewho are not the same person but who are also
matched in terms of gender, residence, age and heart condition.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
The same with Laura, Rachel, and Kate who are also matched in terms of gender, residence, age
and heart condition.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
The same with Laura, Rachel, and Kate who are also matched in terms of gender, residence, age
and heart condition.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
And Lynn, Ed, and Kade who are also matched in terms of gender, residence, age and heart
condition.
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
June Hours
of sleep
July Hours of
sleep
August Hours of
sleep
Males from Minnesota
over 65 with heart
disease
Bob 5 Tanner 6 Mckay 5
Males from California
over 65 without heart
disease
Ashton 4 Roger 3 Steve 4
Females from Utah under
65 with heart disease
Laura 5 Rachel 6 Kate 6
Males from Texas under
65 with lung disease
Lynn 7 Ed 8 Kade 8
And Lynn, Ed, and Kade who are also matched in terms of gender, residence, age and heart
condition.
In summary,
In summary,
With repeated samples you are measuring either the same people over time or the same kind of person over time (matched)
Once again, independent samples are samples that have different research subjects.
Once again, independent samples are samples that have different research subjects.
Repeated samples have the same research subjects, that are measured over multiple times.
Once again, independent samples are samples that have different research subjects.
Repeated samples have the same research subjects, that are measured over multiple times.
Repeated samples can have different research subjects if those research subjects are matched in some way. They are also measured over time.
In this Guided Practice you will be presented with two word problems. You will be asked to determine if the word problem is depicting an independent or repeated measure samples.
Problem #1
Problem #1
Auto-engineers equip twelve cars with a special brand of radial tires. These vehicles were then driven over a test course. Then the same 12 cars were equipped with regular belted tires and driven over the same course. After each run, the cars’ miles per gallon was measured.
Is this studying dealing with independent samples or repeated measures?
Problem #1
Auto-engineers equip twelve cars with a special brand of radial tires. These vehicles were then driven over a test course. Then the same 12 cars were equipped with regular belted tires and driven over the same course. After each run, the cars’ miles per gallon was measured.
Is this studying dealing with independent samples or repeated measures?
Problem #1
Auto-engineers equip twelve cars with a special brand of radial tires. These vehicles were then driven over a test course. Then the same 12 cars were equipped with regular belted tires and driven over the same course. After each run, the cars’ miles per gallon was measured.
A. independent samplesB. repeated measures
Is this studying dealing with independent samples or repeated measures?
Problem #1
Auto-engineers equip twelve cars with a special brand of radial tires. These vehicles were then driven over a test course. Then the same 12 cars were equipped with regular belted tires and driven over the same course. After each run, the cars’ miles per gallon was measured.
A. independent samplesB. repeated measures
Problem #1
Auto-engineers equip twelve cars with a special brand of radial tires. These vehicles were then driven over a test course. Then the same 12 cars were equipped with regular belted tires and driven over the same course. After each run, the cars’ miles per gallon was measured.
A. independent samplesB. repeated measures
The reason we are dealing with a repeated measures sample here is because the SAME vehicles are being tested twice. The only difference between the two
times is the type of tires that were used.
Problem #1
Auto-engineers equip twelve cars with a special brand of radial tires. These vehicles were then driven over a test course. Then the same 12 cars were equipped with regular belted tires and driven over the same course. After each run, the cars’ miles per gallon was measured.
A. independent samplesB. repeated measures
The reason we are dealing with a repeated measures sample here is because the SAME vehicles are being tested twice. The only difference between the two
times is the type of tires that were used.
Problem #1
Auto-engineers equip twelve cars with a special brand of radial tires. These vehicles were then driven over a test course. Then the same 12 cars were equipped with regular belted tires and driven over the same course. After each run, the cars’ miles per gallon was measured.
A. independent samplesB. repeated measures
The reason we are dealing with a repeated measures sample here is because the SAME vehicles are being tested twice. The only difference between the two
times is the type of tires that were used.
Problem #1
Auto-engineers equip twelve cars with a special brand of radial tires. These vehicles were then driven over a test course. Then the same 12 cars were equipped with regular belted tires and driven over the same course. After each run, the cars’ miles per gallon was measured.
A. independent samplesB. repeated measures
The reason we are dealing with a repeated measures sample here is because the SAME vehicles are being tested twice. The only difference between the two
times is the type of tires that were used.
Problem #1
Auto-engineers equip twelve cars with a special brand of radial tires. These vehicles were then driven over a test course. Then the same 12 cars were equipped with regular belted tires and driven over the same course. After each run, the cars’ miles per gallon was measured.
A. independent samplesB. repeated measures
The reason we are dealing with a repeated measures sample here is because the SAME vehicles are being tested twice. The only difference between the two
times is the type of tires that were used.
First Time
Problem #1
Auto-engineers equip twelve cars with a special brand of radial tires. These vehicles were then driven over a test course. Then the same 12 cars were equipped with regular belted tires and driven over the same course. After each run, the cars’ miles per gallon was measured.
A. independent samplesB. repeated measures
The reason we are dealing with a repeated measures sample here is because the SAME vehicles are being tested twice. The only difference between the two
times is the type of tires that were used.
Problem #1
Auto-engineers equip twelve cars with a special brand of radial tires. These vehicles were then driven over a test course. Then the same 12 cars were equipped with regular belted tires and driven over the same course. After each run, the cars’ miles per gallon was measured.
A. independent samplesB. repeated measures
The reason we are dealing with a repeated measures sample here is because the SAME vehicles are being tested twice. The only difference between the two
times is the type of tires that were used.
Problem #1
Auto-engineers equip twelve cars with a special brand of radial tires. These vehicles were then driven over a test course. Then the same 12 cars were equipped with regular belted tires and driven over the same course. After each run, the cars’ miles per gallon was measured.
A. independent samplesB. repeated measures
The reason we are dealing with a repeated measures sample here is because the SAME vehicles are being tested twice. The only difference between the two
times is the type of tires that were used.
Second Time
Problem #2
Problem #2
A manager wishes to determine whether the time required to complete a certain task differs for the three groups: Beginners, intermediate, and advanced trained employees.
Problem #2
A manager wishes to determine whether the time required to complete a certain task differs for the three groups: Beginners, intermediate, and advanced trained employees.
Is this studying dealing with independent samples or repeated measures?
Problem #2
A manager wishes to determine whether the time required to complete a certain task differs for the three groups: Beginners, intermediate, and advanced trained employees.
A. independent samplesB. repeated measures
Is this studying dealing with independent samples or repeated measures?
Problem #2
A manager wishes to determine whether the time required to complete a certain task differs for the three groups: Beginners, intermediate, and advanced trained employees.
A. independent samplesB. repeated measures
Is this studying dealing with independent samples or repeated measures?
Problem #2
A manager wishes to determine whether the time required to complete a certain task differs for the three groups: Beginners, intermediate, and advanced trained employees.
A. independent samplesB. repeated measures
The reason we are dealing with an independent sample here is because we are comparing the time required to complete certain tasks between three
different and unmatched groups.
Problem #2
A manager wishes to determine whether the time required to complete a certain task differs for the three groups: Beginners, intermediate, and advanced trained employees.
A. independent samplesB. repeated measures
The reason we are dealing with an independent sample here is because we are comparing the time required to complete certain tasks between three
different and unmatched groups.
Problem #2
A manager wishes to determine whether the time required to complete a certain task differs for the three groups: Beginners, intermediate, and advanced trained employees.
A. independent samplesB. repeated measures
The reason we are dealing with an independent sample here is because we are comparing the time required to complete certain tasks between three
different and unmatched groups.
Problem #2
A manager wishes to determine whether the time required to complete a certain task differs for the three groups: Beginners, intermediate, and advanced trained employees.
A. independent samplesB. repeated measures
The reason we are dealing with an independent sample here is because we are comparing the time required to complete certain tasks between three
different and unmatched groups.
Problem #2
A manager wishes to determine whether the time required to complete a certain task differs for the three groups: Beginners, intermediate, and advanced trained employees.
A. independent samplesB. repeated measures
The reason we are dealing with an independent sample here is because we are comparing the time required to complete certain tasks between three
different and unmatched groups.
Finally, there are scenarios where the problem you are working on will have both repeated and independent samples at the same time.
In the slides that follow, we will use an example similar to one you have already seen in this presentation:
You have been asked to determine the effect of a new vocabulary enhancing therapy on younger, middle age and older people. You collect two samples of each group (younger, middle age, older). All six groups (2 young, 2 middle, 2 old) are administered a pre-vocabulary test. The first set of younger, middle age, and older samples receives the vocab-enhancing therapy. The second set of groups does not. After three months of therapy all six groups take a post-vocabulary test.
First, determine if there is a statistically significant difference between each of the control and treatment groups on just the pre-test.
Second, determine if there is a statistically significant difference between the pre and posttest for each group.
You have been asked to determine the effect of a new vocabulary enhancing therapy on younger, middle age and older people. You collect two samples of each group (younger, middle age, older). All six groups (2 young, 2 middle, 2 old) are administered a pre-vocabulary test. The first set of younger, middle age, and older samples receives the vocab-enhancing therapy. The second set of groups does not. After three months of therapy all six groups take a post-vocabulary test.
First, determine if there is a statistically significant difference between each of the control and treatment groups on just the pre-test.
Second, determine if there is a statistically significant difference between the pre and posttest for each group.
You have been asked to determine the effect of a new vocabulary enhancing therapy on younger, middle age and older people. You collect two samples of each group (younger, middle age, older). All six groups (2 young, 2 middle, 2 old) are administered a pre-vocabulary test. The first set of younger, middle age, and older samples receives the vocab-enhancing therapy. The second set of groups does not. After three months of therapy all six groups take a post-vocabulary test..
First, determine if there is a statistically significant difference between each of the control and treatment groups on just the pre-test.
Second, determine if there is a statistically significant difference between the pre and posttest for each group.
You have been asked to determine the effect of a new vocabulary enhancing therapy on younger, middle age and older people. You collect two samples of each group (younger, middle age, older). All six groups (2 young, 2 middle, 2 old) are administered a pre-vocabulary test. The first set of younger, middle age, and older samples receives the vocab-enhancing therapy. The second set of groups does not. After three months of therapy all six groups take a post-vocabulary test.
First, determine if there is a statistically significant difference between each of the control and treatment groups on just the pre-test.
Second, determine if there is a statistically significant difference between the pre and posttest for each group.
You have been asked to determine the effect of a new vocabulary enhancing therapy on younger, middle age and older people. You collect two samples of each group (younger, middle age, older). All six groups (2 young, 2 middle, 2 old) are administered a pre-vocabulary test. The first set of younger, middle age, and older samples receives the vocab-enhancing therapy. The second set of groups does not. After three months of therapy all six groups take a post-vocabulary test.
First, determine if there is a statistically significant difference between each of the control and treatment groups on just the pre-test.
Second, determine if there is a statistically significant difference between the pre and posttest for each group.
Wow, this is a lot of information!
Let’s put it in a table.
Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young 5 10
2 Young 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 10
2 Young Control 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab Test Scores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab Test Scores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab Test Scores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab Test Scores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
So, how are these both independent and repeated samples
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
The samples that are independent are all six groups, because if you are in group 1 you are
not in group 2, group 3, group 4, 5, 6 etc.
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
The samples that are independent are all six groups, because if you are in group 1 you are
not in group 2, group 3, group 4, 5, 6 etc.
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
The samples that are independent are all six groups, because if you are in group 1 you are
not in group 2, group 3, group 4, 5, 6 etc.
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
The samples that are independent are all six groups, because if you are in group 1 you are
not in group 2, group 3, group 4, 5, 6 etc.
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
The samples that are independent are all six groups, because if you are in group 1 you are
not in group 2, group 3, group 4, 5, 6 etc.
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
The samples that are independent are all six groups, because if you are in group 1 you are
not in group 2, group 3, group 4, 5, 6 etc.
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
The samples that are independent are all six groups, because if you are in group 1 you are
not in group 2, group 3, group 4, 5, 6 etc.
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
All six groups are independent of one another.
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
All six groups are independent of one another.
Each group is repeated within itself because the same persons (e.g., young treatment group) are
measured twice or repeatedly
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Each group is repeated within itself because the same persons (e.g., young treatment group) are
measured twice or repeatedly
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Each group is repeated within itself because the same persons (e.g., young treatment group) are
measured twice or repeatedly
1st Test
Groups Age Treatment / Control
Pre-Vocab Test Scores
Post-Vocab TestScores
1 Young Treatment 5 10
2 Young Control 6 7
3 Middle Treatment 19 26
4 Middle Control 21 23
5 Old Treatment 12 24
6 Old Control 13 16
Each group is repeated within itself because the same persons (e.g., young treatment group) are
measured twice or repeatedly
2nd Test
This is an example of both repeated and independent samples in the same problem.
Look at the problem you are working on and determine if the samples are independent or repeated:
Look at the problem you are working on and determine if the samples are independent or repeated:
Independent Samples
Both Repeated & Independent Samples
