is the data scaled, ordinal, or nominal proportional?
DESCRIPTION
Decision-Based Learning - Is the Data Scaled, Ordinal, or Nominal Proportional?TRANSCRIPT
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This presentation will assist you in determining if the data associated with the problem you are working on
![Page 2: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/2.jpg)
This presentation will assist you in determining if the data associated with the problem you are working on
Participant Score
A 10
B 11
C 12
D 12
E 12
F 13
G 14
![Page 3: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/3.jpg)
This presentation will assist you in determining if the data associated with the problem you are working on
Participant Score
A 10
B 11
C 12
D 12
E 12
F 13
G 14
![Page 4: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/4.jpg)
This presentation will assist you in determining if the data associated with the problem you are working on is:
![Page 5: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/5.jpg)
This presentation will assist you in determining if the data associated with the problem you are working on is:
Scaled
![Page 6: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/6.jpg)
This presentation will assist you in determining if the data associated with the problem you are working on is:
Scaled
Ordinal
![Page 7: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/7.jpg)
This presentation will assist you in determining if the data associated with the problem you are working on is:
Scaled
Ordinal
Nominal Proportional
![Page 8: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/8.jpg)
First, a little background
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With inferential statistics you will use either parametric or nonparametric methods.
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What is a parametric method?
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Parametric methods use story telling tools like center (what is the average height?), spread (how big is the difference between the shortest and tallest person?), or association (what is the relationship between height and weight?) in a sample to generalize to a population.
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Parametric methods use story telling tools like center (what is the relationship between height and weight?) in a sample to generalize to a population.
![Page 13: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/13.jpg)
Parametric methods use story telling tools like center (e.g., what is the average height?), spread (how big is the difference between the shortest and tallest person?), or association (what is the relationship between height and weight?) in a sample to generalize to a population.
![Page 14: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/14.jpg)
Parametric methods use story telling tools like center (what is the average height?), spread (how big is the difference between the shortest and tallest person?), or association (what is the relationship between height and weight?) in a sample to generalize to a population.
![Page 15: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/15.jpg)
Parametric methods use story telling tools like center (what is the average height?), spread (e.g., how big is the difference between the shortest and tallest person?), or association (what is the relationship between height and weight?) in a sample to generalize to a population.
![Page 16: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/16.jpg)
Parametric methods use story telling tools like center (what is the average height?), spread (how big is the difference between the shortest and tallest person?), or association (what is the relationship between height and weight?) in a sample to generalize to a population.
![Page 17: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/17.jpg)
Parametric methods use story telling tools like center (what is the average height?), spread (how big is the difference between the shortest and tallest person?), or association (e.g., what is the relationship between height and weight?). in a sample to generalize to a population.
![Page 18: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/18.jpg)
Parametric methods use story telling tools like center (what is the average height?), spread (how big is the difference between the shortest and tallest person?), or association (e.g., what is the relationship between height and weight?) in a sample to generalize to a population.
![Page 19: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/19.jpg)
Parametric methods use these story telling tools (center, spread, association) in a sample
![Page 20: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/20.jpg)
Parametric methods use these story telling tools (center, spread, association) in a sample
SAMPLE
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Parametric methods use these story telling tools (center, spread, association) in a sampleto generalize to
SAMPLE
![Page 22: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/22.jpg)
Parametric methods use these story telling tools (center, spread, association) in a sample to generalize to
SAMPLEgeneralize to
![Page 23: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/23.jpg)
Parametric methods use these story telling tools (center, spread, association) in a sample to generalize to a population.
SAMPLEgeneralize to
![Page 24: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/24.jpg)
Parametric methods use these story telling tools (center, spread, association) in a sample to generalize to a population.
SAMPLEgeneralize to
POPULATION
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We ask . . .
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We ask . . .
what is the probability that what's happening in a sample,
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We ask . . .
what is the probability that what's happening in a sample,
SAMPLE:center, spread,
association
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We ask . . .
what is the probability that what's happening in a sample, is happening in
SAMPLE:center, spread,
association
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We ask . . .
what is the probability that what's happening in a sample, is happening in
SAMPLE:center, spread,
association
![Page 30: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/30.jpg)
We ask . . .
what is the probability that what's happening in a sample, is happening in a population.
SAMPLE:center, spread,
association
![Page 31: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/31.jpg)
We ask . . .
what is the probability that what's happening in a sample, is happening in a population.
SAMPLE:center, spread,
association
POPULATION: center, spread, association
![Page 32: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/32.jpg)
To make that kind of leap (from sample to population) requires that certain conditions are met.
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To make that kind of leap (from sample to population) requires that certain conditions are met.
Conditions or assumptions that must be met
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These are called parametric CONDITIONS or ASSUMPTIONS
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The first condition is that the data be scaled
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What is scaled data?
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What is scaled data?
Note – scaled data has two subcategories (1) interval data (no zero point but equal
intervals) and (2) ratio data (a zero point and equal
intervals)
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What is scaled data?
For the purposes of this presentation we will not discuss these further but just focus on both as scaled data.
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What is scaled data?
Participant Score
A 10
B 11
C 12
D 12
E 12
F 13
G 14
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Scaled data is data that has a couple of attributes.
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We will describe those attributes with illustrations from a scaled variable:
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We will describe those attributes with illustrations from a scaled variable: Temperature.
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Attribute #1 – scaled data assume a quantity.
Meaning that 2 is more than 3 and 4 is more than 3 and 20 is less than 30, etc.
For example: 40 degrees is more than 30 degrees. 110 degrees isless than 120 degrees.
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Attribute #1 – scaled data assume a quantity.
Meaning that 2 is more than 3 and 4 is more than 3 and 20 is less than 30, etc.
For example: 40 degrees is more than 30 degrees. 110 degrees isless than 120 degrees.
![Page 45: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/45.jpg)
Attribute #1 – scaled data assume a quantity.
Meaning that 3 is more than 2 and 4 is more than 3 and 20 is less than 30, etc.
For example: 40 degrees is more than 30 degrees. 110 degrees isless than 120 degrees.
![Page 46: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/46.jpg)
Attribute #1 – scaled data assume a quantity.
Meaning that 3 is more than 2 and 4 is more than 3 and 20 is less than 30, etc.
For example: 40 degrees is more than 30 degrees. 110 degrees isless than 120 degrees.
![Page 47: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/47.jpg)
Attribute #1 – scaled data assume a quantity.
Meaning that 3 is more than 2 and 4 is more than
3 and 20 is less than 30, etc.
For example: 40 degrees is more than 30 degrees. 110 degrees isless than 120 degrees.
![Page 48: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/48.jpg)
Attribute #1 – scaled data assume a quantity.
Meaning that 3 is more than 2 and 4 is more than 3 and 20 is less than 30, etc.
For example: 40 degrees is more than 30 degrees. 110 degrees isless than 120 degrees.
100 degrees is more than 40 degrees
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Attribute #1 – scaled data assume a quantity.
Meaning that 3 is more than 2 and 4 is more than 3 and 20 is less than 30, etc.
For example: 40 degrees is more than 30 degrees. 110 degrees isless than 120 degrees.
60 degrees is less than 80 degrees
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Attribute #1 – scaled data assume a quantity.
Meaning that 3 is more than 2 and 4 is more than 3 and 20 is less than 30, etc.
For example: 40 degrees is more than 30 degrees. 110 degrees isless than 120 degrees.
60 degrees is less than 80 degrees
If the data represents varying amounts then this is the first requirement for data to be
considered - scaled.
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Attribute #2
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Attribute #2 – scaled data has equal intervals or each unit has the same value.
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Attribute #2 – scaled data has equal intervals or each unit has the same value.
Meaning the distance between 1 and 2 is the same as
the distance between 14 and 15 or 1,123 and
1,124.
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Attribute #2 – scaled data has equal intervals or each unit has the same value.
Meaning the distance between 1 and 2 is the same as
the distance between 14 and 15 or 1,123 and
1,124. They all have a unit value of 1 between them.
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In our temperature example:
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40o - 41o
100o - 101o
70o – 71o
Each set of readings are the same distance
apart: 1o
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40o - 41o
100o - 101o
70o – 71o
Each set of readings are the same distance
apart: 1o
The point here is that each unit value is the same across the
entire scale of numbers
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40o - 41o
100o - 101o
70o – 71o
Each set of readings are the same distance
apart: 1o
Note, this is not the case with ordinal numbers where 1st place in a marathon might be 2:03 hours, 2nd place 2:05 and 3rd place 2:43.
They are not equally spaced!
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What does a scaled data set look like?
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Here are some examples:
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Height
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HeightPersons HeightCarly 5’ 3”Celeste 5’ 6”Donald 6’ 3”Dunbar 6’ 1”Ernesta 5’ 4”
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Height
Attribute #1: We are dealing with amounts
Persons HeightCarly 5’ 3”Celeste 5’ 6”Donald 6’ 3”Dunbar 6’ 1”Ernesta 5’ 4”
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HeightPersons HeightCarly 5’ 3”Celeste 5’ 6”Donald 6’ 3”Dunbar 6’ 1”Ernesta 5’ 4”
Attribute #2: There are equal intervals across the scale. One inch is the same value regardless of where you are on the scale.
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Intelligence Quotient (IQ)
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Intelligence Quotient (IQ)Persons Height IQCarly 5’ 3” 120Celeste 5’ 6” 100Donald 6’ 3” 95Dunbar 6’ 1” 121Ernesta 5’ 4” 103
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Intelligence Quotient (IQ)Persons Height IQCarly 5’ 3” 120Celeste 5’ 6” 100Donald 6’ 3” 95Dunbar 6’ 1” 121Ernesta 5’ 4” 103
Attribute #1: We are dealing with amounts
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Intelligence Quotient (IQ)Persons Height IQCarly 5’ 3” 120Celeste 5’ 6” 100Donald 6’ 3” 95Dunbar 6’ 1” 121Ernesta 5’ 4” 103
Attribute #2: Supposedly there are equal intervals across this scale. A little harder to prove but most researchers go with it.
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Pole Vaulting Placement
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Pole Vaulting PlacementPersons Height IQ PVPCarly 5’ 3” 120 3rd
Celeste 5’ 6” 100 5th
Donald 6’ 3” 95 1st
Dunbar 6’ 1” 121 4th
Ernesta 5’ 4” 103 2nd
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Pole Vaulting PlacementPersons Height IQ PVPCarly 5’ 3” 120 3rd
Celeste 5’ 6” 100 5th
Donald 6’ 3” 95 1st
Dunbar 6’ 1” 121 4th
Ernesta 5’ 4” 103 2nd
Attribute #1: We are dealing with amounts
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Pole Vaulting PlacementPersons Height IQ PVPCarly 5’ 3” 120 3rd
Celeste 5’ 6” 100 5th
Donald 6’ 3” 95 1st
Dunbar 6’ 1” 121 4th
Ernesta 5’ 4” 103 2nd
Attribute #2: We are NOT dealing with equal intervals. 1st place (16’0”) and 2nd place (15’8”) are not the same distance from one another as 2nd Place and 3rd place (12’2”).
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Based on this explanation is your data scaled?
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If your data is scaled as shown in these examples, select
![Page 75: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/75.jpg)
If your data is scaled as shown in these examples, select
Scaled
Ordinal
Nominal Proportional
![Page 76: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/76.jpg)
We have now demonstrated scaled data and given you a brief introduction to ordinal data.
![Page 77: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/77.jpg)
Once again, ordinal data is data that is ranked:
![Page 78: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/78.jpg)
Once again, ordinal data is data that is ranked:
![Page 79: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/79.jpg)
In other words,
![Page 80: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/80.jpg)
Ordinal scales use numbers to represent relative amounts of an attribute.
![Page 81: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/81.jpg)
Ordinal scales use numbers to represent relative amounts of an attribute.
1st Place16’ 3”
![Page 82: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/82.jpg)
Ordinal scales use numbers to represent relative amounts of an attribute.
1st Place16’ 3”
2nd Place16’ 1”
![Page 83: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/83.jpg)
Ordinal scales use numbers to represent relative amounts of an attribute.
1st Place16’ 3”
2nd Place16’ 1”
3rd Place15’ 2”
![Page 84: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/84.jpg)
Ordinal scales use numbers to represent relative amounts of an attribute.
3rd Place15’ 2”
2nd Place16’ 1”
1st Place16’ 3”
Relative Amounts of Bar Height
![Page 85: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/85.jpg)
Example of relative amounts of authority
![Page 86: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/86.jpg)
Corporal2
Sargent3
Lieutenant4
Major5
Colonel6
General7
Private1
Example of relative amounts of authority
![Page 87: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/87.jpg)
Corporal2
Sargent3
Lieutenant4
Major5
Colonel6
General7
Private1
Notice how we are dealing with amounts of authority
Example of relative amounts of authority
![Page 88: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/88.jpg)
Corporal2
Sargent3
Lieutenant4
Major5
Colonel6
General7
Private1
But,
Example of relative amounts of authority
![Page 89: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/89.jpg)
Corporal2
Sargent3
Lieutenant4
Major5
Colonel6
General7
Private1
But, they are not equally spaced.
Example of relative amounts of authority
![Page 90: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/90.jpg)
Corporal2
Sargent3
Lieutenant4
Major5
Colonel6
General7
Private1
But, they are not equally spaced.
Example of relative amounts of authority
![Page 91: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/91.jpg)
Corporal2
Sargent3
Lieutenant4
Major5
Colonel6
General7
Private1
But, they are not equally spaced.
Example of relative amounts of authority
![Page 92: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/92.jpg)
You can tell if you have an ordinal data set when the data is described as ranks.
![Page 93: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/93.jpg)
You can tell if you have an ordinal data set when the data is described as ranks.
Persons Pole Vault Placement
Carly 3rd
Celeste 5th
Donald 1st
Dunbar 4th
Ernesta 2nd
![Page 94: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/94.jpg)
Or in percentiles
![Page 95: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/95.jpg)
Or in percentiles
Persons ACT Percentile
RankCarly 55%Celeste 23%Donald 97%Dunbar 37%Ernesta 78%
![Page 96: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/96.jpg)
If your data is ranked as shown in these examples, select
![Page 97: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/97.jpg)
If your data is ranked as shown in these examples, select
Scaled
Ordinal
Nominal Proportional
![Page 98: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/98.jpg)
Finally, let’s see what data looks like when it is nominal proportional:
![Page 99: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/99.jpg)
Nominal data is different from scaled or ordinal,
![Page 100: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/100.jpg)
Nominal data is different from scaled or ordinal, because they do not deal with amounts
![Page 101: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/101.jpg)
Nominal data is different from scaled or ordinal, because they do not deal with amounts nor equal intervals.
![Page 102: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/102.jpg)
For example,
![Page 103: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/103.jpg)
Nationality is a variable that does not have amounts nor equal intervals.
![Page 104: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/104.jpg)
1 = Canadian
2 = American
![Page 105: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/105.jpg)
1 = Canadian
2 = American
Being Canadian is not numerically or quantitatively more than being
American
![Page 106: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/106.jpg)
1 = Canadian
2 = American
The numbers 1 and 2 do not represent amounts. They are just a way to distinguish the two groups numerically.
![Page 107: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/107.jpg)
We could have just as easily used 1s for Americans and 2s for Canadians
![Page 108: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/108.jpg)
We could have just as easily used 1s for Americans and 2s for Canadians
1 = Canadian
2 = American
![Page 109: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/109.jpg)
We could have just as easily used 1s for Americans and 2s for Canadians
1 = American
2 = Canadian
![Page 110: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/110.jpg)
Other examples:
![Page 111: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/111.jpg)
Religious Affiliation
![Page 112: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/112.jpg)
Religious Affiliation1 - Buddhist
2 - Catholic
3 - Jew
4 - Mormon
5 - Muslim
6 - Protestant
![Page 113: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/113.jpg)
Gender
![Page 114: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/114.jpg)
Gender1 - Male
2 - Female
![Page 115: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/115.jpg)
Preference
![Page 116: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/116.jpg)
Preference:
1. People who prefer chocolate ice-cream
![Page 117: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/117.jpg)
Preference:
1. People who prefer chocolate ice-cream
2. People who dislike chocolate ice-cream
![Page 118: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/118.jpg)
Pass/Fail
![Page 119: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/119.jpg)
Pass/Fail
1. Those who passed the test
![Page 120: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/120.jpg)
Pass/Fail
1. Those who passed the test
2. Those who failed the test
![Page 121: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/121.jpg)
The word “Nom” in “nominal” means “name”.
![Page 122: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/122.jpg)
The word “Nom” in nominal means “name”. Essentially we are using data to name, identify, distinguish, classify or categorize.
![Page 123: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/123.jpg)
Other names for nominal data are categorical or frequency data.
![Page 124: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/124.jpg)
Here is how the nominal data would look like in a data set:
![Page 125: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/125.jpg)
Here is how the nominal data would look like in a data set:
PersonsCarlyCelesteDonaldDunbarErnesta
![Page 126: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/126.jpg)
Here is how the nominal data would look like in a data set:
Persons GenderCarlyCelesteDonaldDunbarErnesta
![Page 127: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/127.jpg)
Here is how the nominal data would look like in a data set:
Persons GenderCarlyCelesteDonaldDunbarErnesta
1 = Male2 = Female
![Page 128: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/128.jpg)
Here is how the nominal data would look like in a data set:
Persons GenderCarly 2Celeste 2Donald 1Dunbar 1Ernesta 2
1 = Male2 = Female
![Page 129: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/129.jpg)
Persons Gender PreferenceCarly 2Celeste 2Donald 1Dunbar 1Ernesta 2
![Page 130: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/130.jpg)
Persons Gender PreferenceCarly 2Celeste 2Donald 1Dunbar 1Ernesta 2
1 = Like ice-cream2 = Don’t like ice-cream
![Page 131: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/131.jpg)
Persons Gender PreferenceCarly 2 1Celeste 2 1Donald 1 1Dunbar 1 2Ernesta 2 2
1 = Like ice-cream2 = Don’t like ice-cream
![Page 132: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/132.jpg)
Persons Gender PreferenceCarly 2 1Celeste 2 1Donald 1 1Dunbar 1 2Ernesta 2 2
Religion
![Page 133: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/133.jpg)
Persons Gender PreferenceCarly 2 1Celeste 2 1Donald 1 1Dunbar 1 2Ernesta 2 2
Religion
1 - Buddhist2 - Catholic3 - Jew4 - Mormon5 - Muslim6 - Protestant
![Page 134: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/134.jpg)
Persons Gender PreferenceCarly 2 1Celeste 2 1Donald 1 1Dunbar 1 2Ernesta 2 2
Religion42561
1 - Buddhist2 - Catholic3 - Jew4 - Mormon5 - Muslim6 - Protestant
![Page 135: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/135.jpg)
Now that we know what nominal data is,
![Page 136: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/136.jpg)
What is nominal proportional data?
![Page 137: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/137.jpg)
What is nominal proportional data?
Scaled
Ordinal
Nominal Proportional
![Page 138: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/138.jpg)
Nominal proportional data is simply the proportion of individuals who are in one category as opposed to another.
![Page 139: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/139.jpg)
For example,
![Page 140: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/140.jpg)
In the data set below:
![Page 141: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/141.jpg)
In the data set below:
Persons GenderCarly 2Celeste 2Donald 1Dunbar 1Ernesta 2
![Page 142: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/142.jpg)
Persons GenderCarly 2Celeste 2Donald 1Dunbar 1Ernesta 2
3 out of 5 persons are female
![Page 143: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/143.jpg)
Persons GenderCarly 2Celeste 2Donald 1Dunbar 1Ernesta 2
Or 60% are female
![Page 144: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/144.jpg)
Persons GenderCarly 2Celeste 2Donald 1Dunbar 1Ernesta 2
That means 2 out of 5 are male
![Page 145: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/145.jpg)
Persons GenderCarly 2Celeste 2Donald 1Dunbar 1Ernesta 2
Or 40% are male
![Page 146: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/146.jpg)
In such cases you may not see a data set,
![Page 147: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/147.jpg)
you may just see a question like this:
![Page 148: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/148.jpg)
A claim is made that four out of five veterans (or 80%) are supportive of the current conflict. After you sample five veterans you find that three out of five (or 60%) are supportive. In terms of statistical significance does this result support or invalidate this claim?
![Page 149: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/149.jpg)
If you were to put these results in a data set it would look like this:
![Page 150: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/150.jpg)
VeteransABCDE
![Page 151: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/151.jpg)
Veterans SupportiveABCDE
![Page 152: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/152.jpg)
Veterans SupportiveABCDE
1 = supportive2 = not supportive
![Page 153: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/153.jpg)
Veterans SupportiveA 2B 2C 1D 1E 1
1 = supportive2 = not supportive
![Page 154: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/154.jpg)
Veterans SupportiveA 2B 2C 1D 1E 1
1 = supportive2 = not supportive
If the question is stated in terms of percentages (e.g., 60% of veterans were supportive), then that percentage is nominal proportional data
![Page 155: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/155.jpg)
If your data is nominal proportional as shown in these examples, select
![Page 156: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/156.jpg)
If your data is nominal proportional as shown in these examples, select
Scaled
Ordinal
Nominal Proportional
![Page 157: Is the Data Scaled, Ordinal, or Nominal Proportional?](https://reader035.vdocument.in/reader035/viewer/2022081518/54817911b4af9f1f518b4627/html5/thumbnails/157.jpg)
That concludes this explanation of scaled, ordinal and nominal proportional data.