KIN 610: Statistics/Scales & Types
(pages 5 & 6 in Vincent text)

Scale “Identification” of Variables:

1. Nominal
2. Ordinal

• These two are for non-numerical data or numerical data that is treated as a category.  They are usually “discrete”

3. Ratio (most of the time continuous scales will be ratio)
4. Interval

• These two are usually “continuous”

Scale “Types” of Variables:

1. Discrete (things that you count with numbers or categories)
2. Continuous

General Definitions Related to Scales & Types

Variable: A characteristic of a person, place, or thing that can assume more than one value.

VARIABLE “SCALES” OF MEASUREMENT

Interval Level of Measurement: (Continuous)

• “Temperature” would be interval because it is continuous with equally spaced values on a scale.
• Zero does not denote absence of measure.
• There is no proportional comparison among scores i.e. one temperature is not twice as cool or twice as hot as another.
• Keep range narrowed to show realism.

Nominal Level of Measurement: (Discrete)

• Categorical
• Mutually exclusive categories with no qualitative differentiation between the categories.  Data classified this way as groups and called “frequency data” where frequency of each category is listed.

• “Gender” would be nominal because only two categories (or options) and these categories are not ranked or ordered.  Gender is categorical and discreet.  Male and female are mutually exclusive categories. 

Ordinal Level of Measurement: (Discrete)

• Categorical and have “inherent order”
• “Height” would be ordinal because it can only be ranked from highest to lowest and the intervals are NOT evenly spaced.
• Gives quantitative data but doesn’t indicate how much better one score is to the other i.e. your height vs. someone else’s height.
• A nonparametric listing of data based on order without consideration of the absolute value of each data point i.e. listing from highest to lowest or first, second, third, etc.
• “Height” would be ordinal if height was classified as at, above, or below average.  Groupings can be ranked relative to one another.  Intervals are not equally spaced or proportional. 

Ratio Level of Measurement: (Continuous)

• “Age” would be ratio because it’s continuous, units are equally distanced i.e. the time between 3 and 4 years is the same as the time between 7 and 8 years old.
• Values are proportional i.e. 4 years is twice as long as 2 years.
• Time to walk 1 mile was 2.5 minutes vs. another person who walked a mile in 5.0 minutes; it took one person twice as long to walk the same distance so values are proportional.

“TYPES” OF VARIABLES

Continuous Variables: A variable that theoretically can assume any value such as: distance, force, and time.

Discrete Variables: A variable that is limited in its assessment to certain values, usually integers i.e. the data is not continuous; there are gaps between values in the range of data.  Example is gender.

• Variable limited to certain numbers, usually whole numbers and integers such as counting people or heartbeats (can’t have “half a person” or “half a heartbeat”). 

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