Introductory Biostatistics

BS1.2: Types of Variables

OBJECTIVES

At the end of this section you should be able to define types of variables.

VARIABLES:

A sample consists of observations or measurements. Any aspect of an individual that is measured or recorded is called a variable.

It is often useful to define the types of variables, as different statistical methods are applicable to each.

There are two broad categories of variables:

1. Categorical

Binary: Allocation of observations to one of only two possible categories.
Nominal: Allocation of observations into more than two categories.
Ordinal: Allocation of observations into more than two categories that can be ordered.

2. NUMERICAL

Continuous data: A set of data is said to be continuous if the values are measurements that can assume any value within a specified range.
Discrete Data: A set of data is said to be discrete if the values are distinct and separate. That is, they can be counted (1,2,3, ...).

Example:

Binary: Exposed and non-exposed categories / Gender: female/male.
Nominal: Classification of disease / Marital status.
Ordinal: Classification according to mild, moderate and severe.
Continuous: Height / Weight / Systolic / Diastolic BP.
Discrete: Number of new TB cases in a month / Number of patients in a clinic.

General Introduction to Occupational Health: Occupational Hygiene, Epidemiology & Biostatistics by Prof Jonny Myers is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 2.5 South Africa License.