Discover Variables and Field Types
Learning Objectives
After completing this unit, you’ll be able to:
- Identify different types of variables.
- Differentiate between nominal qualitative, ordinal qualitative, and quantitative variables.
- Differentiate between continuous and discrete variables.
Note: Some concepts in this unit are adapted from Heidi Ziemer’s chapter on variables in the online, public domain work, Introduction to Statistics.
Types of Variables
In the Well-Structured Data module you learned that data is organized into columns, or fields, and that in well-structured data fields are made up of variables, one variable per field.
And if you completed the Data Literacy Basics module, you learned that data is made up of both qualitative and quantitative variables. Qualitative variables are variables that cannot be measured numerically, such as categories or characteristics. Quantitative variables are variables that can be measured numerically, such as the number of items in a set. When added to a data set, qualitative variables become qualitative fields (or columns) and quantitative variables become quantitative fields (or columns).
| Name |
Age |
Height | Favorite food |
|---|---|---|---|
| Aliya | 8 | 4'2" | Ice Cream |
| Miles | 12 | 5'3" | Olive Pizza |
| Penny | 42 | 5'7" | Corn on the Cob |
| Vince | 39 | 5'10" | Pancakes |
In the above table, Name and Favorite food are qualitative fields and Age and Height are quantitative fields.
Types of Qualitative Variables
Qualitative variables—variables that can’t be measured numerically—can be further classified into two types: nominal and ordinal.
- Nominal: Nominal qualitative variables are categories that cannot be ranked. For example, let's consider a few types of fruit: bananas, grapes, apricots, and apples. These are nominal variables because there is no implied ranked order among them. A banana, for instance, is not ranked more highly than an apricot.
One way to remember the definition of a nominal variable is: Nominal = Named.
- Ordinal: In contrast to nominal qualitative variables, ordinal qualitative variables can be ranked. They are qualitative because they are not numerically measurable, but there is a logical rank-order among them. For example, think of surveys you may have taken. Examples of ordinal qualitative values on surveys are: Never, Sometimes, Mostly, Always, Extremely dissatisfied, Dissatisfied, Neither satisfied nor dissatisfied, Satisfied, Extremely satisfied.
One way to remember the definition of an ordinal variable is: Ordinal = Ordered.
Note: At times, ordinal values are given numeric equivalents (5 = Extremely satisfied, for example) and then are treated as quantitative values.
Now let's check your understanding. In the following activity, you determine whether each characteristic is a nominal qualitative variable, an ordinal qualitative variable, or a quantitative variable. Drag each set of characteristics to the appropriate category.
Discrete and Continuous Variables
Another classification we can apply to variables includes discrete and continuous variable types.
- Discrete Variables: Discrete variables are individually separate and distinct. Simply stated, if you can count it individually, it is a discrete variable. For example, you can count the number of children in a household individually. A household can have 0 children, 3 children, 6 children, and so on, but it can not have 3.45 children.
The number of toes on a foot and the total number of socks in a drawer are also examples of discrete variables. The total number of toes on all the feet of all the people in your city is even a discrete variable. It would take a long time to individually count all those toes, but it's still possible to do so.
- Continuous Variables: Continuous means forming an unbroken whole, without interruption. These are variables that cannot be counted in a finite amount of time because there is an infinite number of values between any two values. For example, if you want to measure time, every unit of time can be broken into even smaller units: The response time to a stimulus could be expressed as 1.64 seconds, or it could be further broken down and expressed as 1.642378765 seconds, and so on, infinitely. Other examples of continuous values include temperature, distance, and mass.
Use these interactive flashcards to test your understanding of discrete and continuous variables.
Read the example on each card, think about whether it is discrete or continuous, and then click on the card to reveal the correct answer. Click the right-facing arrow to move to the next card, and the left facing arrow to return to the previous card.
In the next unit, you look at how the different variable types are used in data visualizations.
