Types of Quantitative Variables
In the previous sections, we learned about the difference between qualitative and quantitative variables. In the following sections, you’ll learn about how even within these two types of variables, there are different types of values. Here, we’ll focus on the differences found within quantitative variables, which can be either discrete or continuous.
What Are Discrete and Continuous Variables?
On April 10, 2019, the Event Horizon Telescope Collaboration made history. During their worldwide press conference, they unveiled the first image ever taken by humans of a black hole. The Event Horizon Telescope, or EHT for short, combined data from many observatories around the world in order to create the perfect telescope for capturing such a distant object.
Katie Bouman, a computer scientist specializing in the field of computer imagery, was a seminal figure in the creation of the algorithm that would be used for capturing images of black holes. Bouman, like many scientists, had to combine skills from many different disciplines in order to accomplish what was once thought of as impossible. One of these disciplines was, of course, statistics.
Algorithms involved in statistics are generally the same as in computer science - at their most basic, they are simply a set of instructions, usually given to a computer, in order to solve a problem. In the majority of cases, algorithms depend on a fundamental understanding of the different types of quantitative and qualitative variables. While qualitative variables can be divided into nominal and ordinal variables, quantitative variables fall under two distinct categories: discrete and continuous.
Quantitative variables, unlike qualitative variables, are those that are numeric. They typically involve measuring a quantity in a person, place or thing. The easy way to remember the difference between qualitative and quantitative variables is that one measures the qualities of something while the other measures quantities of something. Quantitative variables are also called numeric variables because they often carry numeric information.
Because quantitative variables strive to measure quantities, they are generally divided into discrete and continuous variables. The definition for a discrete variable is that it is countable, finite and numeric. Meaning, it is a number with an identified minimum and maximum.
Continuous variables, on the other hand, are defined as numbers or a numeric date that can take on any value. A numeric date means, for example, 01/01/2019 as opposed to names for days of the week or for months.
Here are some examples that can help you better understand.
An example of a discrete variable can be the number of students in a classroom of 50 students. The minimum is 0 students and the maximum is 50. Let’s say that you decide to record the number of students that show up every day to class. The first day, 20 students are present. The next day, 25 students attend class, and so on. Why is this a discrete variable?
The number of students in this classroom is finite, meaning we know that the total number of students ends at 50. At the same time, we also know they are countable - you can’t count 1.5 of a student or 3/4ths of a student.
Some other examples of discrete variables can be:
- Number of books published in a year
- Number of clothing items in your closet
- Number of protesters at a rally