Data Table Structure

Measurement is the assignment of numbers or codes according to prior-set rules. An observation represents data from an individual study subject. A variable is the generic designation for a measurement (AGE, for instance). A value is a particular realized measurement (e.g., 36).

Data tables are set up so that observations form rows, variables form columns, and values reside in cells:
 
 
VAR1
VAR2
VAR3
Observation1
value
value
value
Observation2
value
value
value
Observation3
value
value
value

It is important to differentiate between variables, values, and observations. Variables represent the thing being measured (e.g., AGE), while values represent realized measurements (e.g., 31). An observation is usually characterized by multiple variables (e.g., AGE, SEX, HEIGHT).

Variables Types

Continuous variable - data comprise numerical scale information in which intervals between numbers are equally spaced (e.g., AGE measured in years); syn: quantitative variable, scale variable, interval variable.

Categorical variable - data comprise named categories (e.g., EYECOLOR classified as brown, blue, or other); syn: qualitative variable, nominal variable.

Ordinal variable - data comprise categories which can be ordered from low to high (e.g., AGREEMENT classified as strongly agree, agree, neutral, disagree, or strongly disagree).