1.3 Types of Variables

There are two basic types of variables: (1) qualitative and (2) quantitative

When the characteristic being studied is nonnumeric, it is called a qualitative variable or an attribute.

Examples of qualitative variables are gender, religious affiliation, type of automobile owned, state of birth, and eye color. When the data are qualitative, we are usually interested in how many or what percent fall in each category. For example, what percent of the population has blue eyes? What percent of the total number of cars sold last month were SUVs?

In statistical research, a variable is defined as an attribute of an object of study. Choosing which variables to measure is central to good experimental design.

If you want to test whether some plant species are more salt-tolerant than others, some key variables you might measure include the amount of salt you add to the water, the species of plants being studied, and variables related to plant health like growth and wilting.

You need to know which types of variables you are working with in order to choose appropriate statistical tests and interpret the results of your study.

Summary of Types of Variables

When the variable studied can be reported numerically, the variable is called a quantitative variable. Examples of quantitative variables are the balance in your checking account, the ages of company presidents, the life of an automobile battery (such as 42 months), and the number of children in a family. Quantitative variables are either discrete or continuous.

Quantitative variables

When you collect quantitative data, the numbers you record represent real amounts that can be added, subtracted, divided, etc. There are two types of quantitative variables: discrete and continuous.