Level of measurement
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Level of measurement (LoM) is an important characteristic of data. The LoM determines what types of descriptive, graphical, and inferential statistical analyses can be used. There are four levels of measurement:
Categorical/nominal[edit | edit source]
- The simplest type of variable is dichotomous (or binary, e.g., 0 = male/ 1 = female; 0 = black/ 1= white; 0 = yes/ 1 = no).
- Categorical or nominal variables simply provide numerical labels (or names) for two or more categories e.g., 0 = red/ 1 = blue/ 2 = green / 3 = yellow; 0 = car; 1 = bus; 2 = bicycle; 3 = aeroplane; 4 = train.
Ordinal[edit | edit source]
- When categorical variables can be meaningfully ordered, they become ordinal variables
- The distance between the ordered categories may vary
- e.g., 1 = 1st, 2 = 2nd, 3 = 3rd in a race; verbal frequency scale (0 = never, 1 = sometimes, 2 = often, 3 = always)
Interval[edit | edit source]
- Ordered categories (discrete values) which have equal distances (e.g., Strongly Disagree - Disagree - Neither Agree or Disagree - Agree - Strongly Agree)
- Allows use of parametrics statistics (which assume a normal distribution)
Ratio[edit | edit source]
- Continuous (not discrete) - values can take on (in theory) infinite decimal points
- Has a meaningful 0 (e.g., the 0 point isn't arbitrary), which allows ratio comparisons (e.g,. according to the sample of participants, males are, on average, 20% taller than females).