Qualitative and Quantitative Data

1. Qualitative Data

Qualitative data is also often called “categorical data”. It is not numerical in the sense that we can do numerical operations with it, like adding numbers together or finding an average, but rather, it fits in the category.

EXAMPLE

Gender: male and female. That's a qualitative variable with two categories.

Letter grades AND zip codes feature numbers, but you wouldn’t necessarily do mathematical equations with them. You wouldn’t find an average zip code, for instance. The purpose of zip codes is to divide areas into categories. Hair color is another example of qualitative data because you can group those with black hair together and put those with blonde hair in another group.

It's important to know that qualitative data can be divided further into two categories:

• Nominal measurements
• Ordinal measurements

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Qualitative/Categorical Data

Data whose values are the names of categories. These can be numbers, but not the kinds of numbers with which it makes sense to do any numerical operations.

1a. Nominal Measurements

EXAMPLE

Favorite color. The order of the listed categories makes no difference. It doesn't matter if you put the colors below in the order of the color spectrum or not.

With nominal data, it only makes sense to reference which category has the largest frequency. In this case, let’s say most people say that green is their favorite color. That is what you would report, and it doesn’t matter that green is the fourth box from the left.

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Nominal Level of Measurement

Qualitative data where the order in which the categories are presented does not matter.

1b. Ordinal Measurements

EXAMPLE

Rating scale. The order of the listed categories is very important because the order is associated with a type of value. It’s very important that you don’t mix up the order here because the circle on the farthest left indicates you are feeling no pain.

With ordinal data, it’s important to keep the order straight, or rather, in order, to express a spectrum ranging from lowest to highest, or worst to best. Ratings like that.

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Ordinal Level of Measurement

Qualitative data where the order in which the categories are presented matters.

2. Quantitative Data

On the other hand, you have quantitative data. Quantitative data are expressed numerically. It makes sense to do numerical operations with it, like finding averages or adding them together.

Examples of quantitative data include:

• Weight
• Commute time to work
• Outdoor temperature

It's important to note that data is displayed differently for qualitative data than with quantitative data. Statistical operations depending on the type of data that we have.

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Quantitative Data

Data whose values are numbers and it makes sense to do numerical operations.

3. Qualitative and Quantitative Data in Practice

Determine if each situation reflects qualitative or quantitative data.

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