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The question of whether education level is nominal or ordinal is a hotly debated one. Here, we’ll take a look at the evidence and try to come to a conclusion.

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## Introduction

In the social sciences, there is often debate about whether a certain variable is nominal or ordinal. Education level is one of those variables. In this article, we will explore the debate and try to come to a conclusion about whether education level is nominal or ordinal.

## What is Nominal Data?

Nominal data is a type of data that is used to label variables without providing any ranking or ordering among the variables. Nominal data is often compared to ordinal data, which does provide ranking or ordering among the variables.

To better understand the difference between nominal and ordinal data, consider the following example. Imagine that you are conducting a survey about favorite colors. respondents are asked to choose their favorite color from a list of colors (e.g., red, blue, yellow, green, etc.). In this case, the colors are the nominal data. The respondents are not asked to rank or order the colors in any way; they simply choose their favorite.

Now imagine that you are conducting a survey about favorite ice cream flavors. respondents are again asked to choose their favorite flavor from a list of flavors (e.g., chocolate, vanilla, strawberry, mint, etc.). However, in this case, the respondents are asked to rank the flavors from 1 (most favorite) to 5 (least favorite). In this example, the flavors are the ordinal data because they are ordered from most to least favorite.

It is important to note that nominal and ordinal data can both be used to label variables; however, only ordinal data can be used to establish relationships among variables because there is an inherent order or ranking involved. Nominal data cannot be used to establish relationships among variables because there is no order or ranking involved.

## What is Ordinal Data?

Ordinal data is a type of categorical data in which the values have a natural, ordered progression. For example, you could ordinal data on a scale from 1-5, with 1 being the lowest and 5 being the highest.

## Examples of Nominal and Ordinal Data

Nominal data is a type of data that consists of a name or label. It is often used to identify items in a set. Ordinal data is a type of data that consists of a name or label and a value. It is often used to rank items in a set.

## How to Analyze Nominal and Ordinal Data

Nominal data is a type of data that consists of names or labels. This type of data can be further divided into two types: categorical and numerical. Categorical data is a type of data that can be divided into groups. For example, gender can be a categorical variable with two groups: male and female. Numerical data is a type of data that consists of numbers. This type of data can be further divided into two types: interval and ratio. Interval data is a type of numerical data that has a defined zero point but no defined maximum or minimum value. For example, temperature can be an interval variable because it has a defined zero point (0 degrees Celsius), but there is no defined maximum or minimum temperature. Ratio data is a type of numerical data that has a defined zero point and a defined maximum and minimum value. For example, length can be a ratio variable because it has a defined zero point (0 centimeters), and there is a defined maximum and minimum length (1 meter).

Ordinal data is a type of data that consists of names or labels that are assigned to categories in order to show the relative position of each category. For example, ranks in the military (e.g., private, sergeant, lieutenant) are ordinal variables because they are assigned in order from lowest to highest rank. Another example of ordinal data is Likert scale responses (e.g., strongly agree, agree, neutral, disagree, strongly disagree).

## Conclusion

Education level is ordinal.