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In statistics, variables can be classified as either **categorical** or **quantitative**.

**Categorical Variables: **Variables that take on names or labels. Examples include:

- Marital status (“married”, “single”, “divorced”)
- Smoking status (“smoker”, “non-smoker”)
- Eye color (“blue”, “green”, “hazel”)
- Level of education (e.g. “high school”, “Bachelor’s degree”, “Master’s degree”)

**Quantitative Variables: **Variables that take on numerical values. Examples include:

- Height of an individual
- Population size of a city
- Number of students in a class
- Number of square feet in a house

The following table summarizes the difference between these two types of variables:

**Examples: Categorical vs. Quantitative Variables**

Use the following examples to gain a better understanding of categorical vs. quantitative variables.

**Example 1: Plant Height**

A botanist walks around a local forest and measures the height of a certain species of plant. The variable **plant height** is a **quantitative variable** because it takes on numerical values. For example, the height could be 15 inches, 17.5 inches, 19.2 inches, etc.

**Example 2: Vacation Locations**

A researcher surveys 200 people and asks them about their favorite vacation location. The variable **vacation location** is a **categorical variable** because it takes on names. For example, responses could include “Miami”, “San Francisco”, “Hilton Head”, etc.

**Example 3: Political Party**

A political scientists surveys 50 people in a certain town and asks them which political party they identify with. The variable **political party** is a **categorical variable** because it takes on labels. For example, responses could include “Democrat”, “Republican”, “Independent”, etc.

**Example 4: Running Times**

A coach records the running times of his 20 track runners. The variable **running time** is a **quantitative variable** because it takes on numerical values. For example, running time could be 58 seconds, 60.343 seconds, 65.4 seconds, etc.

**Example 5: House Prices**

An economist collects data about house prices in a certain city. The variable **house price** is a **quantitative variable** because it takes on numerical values. For example, house price could be $149,000, $289,000, $560,000, etc.

**How to Describe Categorical & Quantitative Variables**

We can summarize **categorical variables** by using frequency tables.

For example, suppose we collect data on the eye color of 100 individuals. Since “eye color” is a categorical variable, we might use the following frequency table to summarize its values:

We can summarize **quantitative variables** using a variety of descriptive statistics.

For example, suppose we collect data on the square footage of 100 homes. Since “square footage” is a quantitative variable, we might use the following descriptive statistics to summarize its values:

**Mean:**1,800**Median:**2,150**Mode:**1,600**Range:**6,500**Interquartile Range:**890**Standard Deviation:**235

These metrics give us an idea of where the center value is located as well as how spread out the values are for this variable.

**Related:** How to Plot Categorical Data in R