# Qualitative vs. Quantitative Variables: What’s the Difference?

In statistics, there are two types of variables:

1. Quantitative Variables: Sometimes referred to as “numeric” variables, these are variables that represent a measurable quantity. Examples include:

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

2. Qualitative Variables: Sometimes referred to as “categorical” variables, these are variables that take on names or labels and can fit into categories. Examples include:

• Eye color (e.g. “blue”, “green”, “brown”)
• Gender (e.g. “male”, “female”)
• Breed of dog (e.g. “lab”, “bulldog”, “poodle”)
• Level of education (e.g. “high school”, “Associate’s degree”, “Bachelor’s degree”)
• Marital status (e.g. “married”, “single”, “divorced”)

Every single variable you will ever encounter in statistics can be classified as either quantitative or qualitative.

### Example: Classifying Quantitative & Qualitative Variables

Consider the following dataset with information about 10 different basketball players:

There are five total variables in this dataset. Two of them are qualitative variables and three of them are quantitative variables:

### Summarizing Quantitative & Qualitative Variables

We can use many different metrics to summarize quantitative variables, including:

However, we can only use frequency tables and relative frequency tables to summarize qualitative variables.

To illustrate this, let’s once again consider the dataset from the previous example:

For the quantiative variable Seasons Played, we can calculate the following metrics:

• Mean: 11.5
• Median: 12
• Mode: 12
• Range: 8
• Interquartile Range: 4.5
• Standard Deviation: 2.915

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

And for the qualitative variable Position, we can create a frequency table to describe how often different values occur:

This table lets us quickly see how frequently each position (G=guard, F=forward, C=center) occurred in the dataset.

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## 3 Replies to “Qualitative vs. Quantitative Variables: What’s the Difference?”

1. Rodger says:

Concise and simple to understand.

2. Srini says:

From a social sciences research perspective, if i have a variable AGE which has 18-30 years numerical values. Another categorical variable “Place of consumption” is having qualitative responses (home, campus, friends). If I want to test association/relation between these two variables of interest,
1. Can I test association between quantitative and qualitative variables?
2. If yes, what tests can I perform?
3. any precautions I need to consider?

3. Turinawe Thomas says:

Good work
Thank you for helping academia