**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/nominalEdit
- 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.

- 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)

- 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)

- 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).

External linksEdit