or What kinda data ya got?
Recall the earlier discussion of types of variables? Nominal variable and ordered variables
Now, let's expand that "ordered" type.
Level | Can be Ranked? | Equal Distance | Zero-Point | Example Variables |
Nominal | No | N/A | N/A | Gender |
Ordinal | Yes | No | N/A | List of most preferred TV shows |
Interval | Yes | Yes | Arbitrary Has + & - | Agreement on Likert-Scale |
Ratio | Yes | Yes | Absolute 0 = absence | Amount of time talking |
Nominal level:
- nominal variables are classified into categories (names)
- They are not arranged in any particular order
- e.g., frequency counts, percentages.
- 48% male and 52% female
- 32% Catholic, 20% Baptist, etc.
Ordinal level:
- categories are ordered from highest to lowest
- e.g., Nielsen ratings (see just the rank data)
- intervals between categories are not standardized
- e.g., frequency counts, percentages
Interval level:
- categories are ranked
- assumed equal distances between ranks
- Arbitrary zero-point
- e.g. temperature - 0 degrees doesn’t mean the absence of temperature. Scale has + & - values.
- Another example: Likert-Scale
Ratio Level:
- categories are ranked
- Equal distances between rank
- Absolute Zero point
- e.g., °F or °C vs. K (Kelvin), age, weight, number of words in a sentence, etc.
What is the connection between a horse race and levels of measurement?
Photo used under Creative Commons.
How would the Mythbusters research (viewed earlier) fit in here? Did they operationalize their variables? How? At what level?
Watch from 0:00 to 10:10.
(Note: If the YouTube clip is no longer available, then the season 8 episode 6 can be found online on Amazon, Netflix, etc., if you are interested.)
Note: The level of measurement (or kind/type of data) you have will determine what statistics you use. More on this later.
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See more about me at my web site WilliamHartPhD.com.
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