Levels of Measurement

Classification that describes the nature of the
information within the values assigned to variables

4 Levels of Measurement

Nominal, Ordinal, Interval & Ratio

Nominal

Categorial variable; values cannot be meaningfully ordered. Assign numbers to objects that are categorized

Nominal Characteristics

1. Categories must be mutually exclusive
2. All categories used to represent the data must be equivalent.
3. The list must be exhaustive.

Examples of Nominal Variables

1. Biological sex (male=1, female =2)
2. Political party affiliation ( 1=democrat,
2=republican, 3=other, 4=not registered)

Nominal Data

Descriptive Statistics & Frequency Distributions

Ordinal

Categorical; Numbers have meaning & are ranked with regard to more or less of a characteristic

Ordinal Characteristics

1. Do not have equal intervals
2. Do not have an absolute zero
3. Number tells the order
4. Distances between attributes have no meaning

Ordinal Examples

1. Socioeconomic Status (1=lower, 2=middle, 3=upper)
2. College Class (1= Freshman, 2= Sophomore, 3= Junior, 4=Senior)

Ordinal Data

Numerical values are assigned to each category with higher numbers representing higher values & the numbers are then related to the variable

Interval Data

Continuous; items are ordered and the size of the intervals between two items on the scale are equal. The distance between attributes has meaning

Interval Examples

1. Temperature measured in Fahrenheit
2. Likert Scales (assuming equal intervals)

Interval Data

Numerical values are assigned to each value and a measure of central tendency is calculated (mean, median, mode)

Ratio

Continuous; items are ordered in an interval scale except there IS a TRUE ZERO & intervals have to be equal

Ratio Examples

1. Number of times you drank soda this week, 0= no soda
2. Number of clients in past 5 months

Ratio Data

Numerical values that are related to the variable are assigned to each category. Higher numbers = "more" of the variable