Quantitative and a Categorical variable
Two types of variables are used in statistics: Quantitative and categorical (also called qualitative): Quantitative variables are numerical variables: counts, percents, or numbers. Categorical variables are descriptions of groups or things, like “breeds of dog” or “voting preference.
What are the differences between quantitative and categorical variables?
Quantitative variables measure some characteristic of interest. Examples include mass, volume, length, temperature, or quantity. The measurements are represented with numbers.
Categorical variables describe but don’t measure, a characteristic of interest. Examples include sex, colour, flavour, marital status, or species. Sometimes categorical data is represented with a number, but that number doesn’t have a mathematical meaning. For example, January can be represented by the number 1, and February by 2, but it doesn’t make sense to perform mathematical operations on them.
How to Distinguish Quantitative and Categorical Variables
When working with statistics, it’s important to understand some of the terminology used, including quantitative and categorical variables and how they differ. The trick is to get a handle on the lingo right from the get-go, so when it comes time to work the problems, you’ll pick up on cues from the wording and get going in the right direction.
Variables can be classified as categorical or quantitative. Categorical variables are those that provide groupings that may have no logical order, or a logical order with inconsistent differences between groups (e.g., the difference between 1st place and 2-second place in a race is not equivalent to the difference between 3rd place and 4th place). Quantitative variables have numerical values with consistent intervals.
Quantitative variables are measured and expressed numerically, have numeric meaning, and can be used in calculations. (That’s why another name for them is numerical variables.) Although zip codes are written in numbers, the numbers are simply convenient labels and don’t have numeric meaning (for example, you wouldn’t add together two zip codes).
A categorical variable doesn’t have numerical or quantitative meaning but simply describes a quality or characteristic of something. The numbers used in categorical or qualitative data designate a quality rather than measurement or quantity. For example, you can assign the number 1 to a person who’s married and the number 2 to a person who isn’t married. The numbers themselves don’t have meaning that is, you wouldn’t add the numbers together. Names or labels (i.e., categories) with no logical order or with a logical order but inconsistent differences between groups (e.g., rankings), also known as qualitative.