Types of Variables
Procedures to summarize data and to perform subsequent analysis differ depending on the type of data (or variables) that are available. As a result, it is important to have a clear understanding of how variables are classified.
There are three general classifications of variables:
1) Discrete Variables: variables that assume only a finite number of values, for example, race categorized as non-Hispanic white, Hispanic, black, Asian, other. Discrete variables may be further subdivided into:
2) Continuous Variables: These are sometimes called quantitative or measurement variables; they can take on any value within a range of plausible values. For example, total serum cholesterol level, height, weight and systolic blood pressure are examples of continuous variables.
3) Time to Event Variables: these reflect the time to a particular event such as a heart attack, cancer remission or death.