You will now determine if the samples you are working with are independent or repeated.

Your options will be:

Your options will be:

Independent Samples

Repeated 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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 6

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

Keaton 5 Kris 6 Phil 6

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

Keaton 5 Kris 6 Phil 6

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

Keaton 5 Kris 6 Phil 6

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

Keaton 5 Kris 6 Phil 6

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

Keaton 5 Kris 6 Phil 6

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

Keaton 5 Kris 6 Phil 6

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

Keaton 5 Kris 6 Phil 6

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

Keaton 5 Kris 6 Phil 6

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

Keaton 5 Kris 6 Phil 6

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

Keaton 5 Kris 6 Phil 6

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

Keaton 5 Kris 6 Phil 6

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

Keaton 5 Kris 6 Phil 6

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

Keaton 5 Kris 6 Phil 6

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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 6

Males from Texas under

65 with lung disease

Lynn 7 Ed 8 Kade 8

The same with Keaton, Kris, and Phil 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

Keaton 5 Kris 6 Phil 6

Males from Texas under

65 with lung disease

Lynn 7 Ed 8 Kade 8

The same with Keaton, Kris, and Phil 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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 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

Keaton 5 Kris 6 Phil 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.

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.

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

Repeated Samples