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Nominal data is labelled into mutually exclusive categories within a variable. These categories cannot be ordered in a meaningful way. For example, pref erred mode of transportation is a nominal variable, because the data is sorted into categories: car, bus, train, tram, bicycle, etc.
Nominal data refers to non-numerical data that is not inherently ordered. It is a sub-type of categorical data, and can include categories like gender, race, and color (Babbie, Halley, & Zaino, 2007). If you’re writing an essay on nominal data, it might be worthwhile quoting a scholarly definition. Here are some good ones I found:
In this post, we define each measurement scale and provide examples of variables that can be used with each scale. Nominal. The simplest measurement scale we can use to label variables is a nominal scale. Nominal scale: A scale used to label variables that have no quantitative values.
As we’ve discussed, nominal data is a categorical data type, so it describes qualitative characteristics or groups, with no order or rank between categories. Examples of nominal data include: In all of these examples, the data options are categorical, and there’s no ranking or natural order.
What is Nominal Data? Nominal data are divided into mutually exclusive categories that do not have a natural order, nor do they provide any quantitative information. The definition of nominal in statistics is “in name only.”
Shared some examples of nominal data: Hair color, nationality, blood type, etc. Introduced descriptive statistics for nominal data: Frequency distribution tables and the measure of central tendency (the mode). Looked at how to visualize nominal data using bar graphs and pie charts.
4) Nominal Data Examples . 5) How can Nominal Data be analysed? 6) Methods to Collect Nominal Data and its Applications . 7) Difference Between Nominal and Ordinal Data . 8) Conclusion . What is Nominal Data? Nominal Data, also known as categorical data, is a type of data used to label variables without providing any quantitative value.
Nominal Data is qualitative data used to name or label variables without providing numeric values. It is the most straightforward form of a level of measurement. Ordinal data is also qualitative data that groups variables into ordered categories.
Nominal data are used to label variables without any quantitative value. Common examples include male/female (albeit somewhat outdated), hair color, nationalities, names of people, and so on. In plain English: basically, they're labels (and nominal comes from "name" to help you remember). You have brown hair (or brown eyes). You are American.
For example: Putting countries into continents. Example: Bulgaria is a country in Europe. Interesting Note: a nominal scale with only two categories (e.g. female/male) is called “dichotomous.” Examples of Nominal Data: Download the above infographic in PDF. Eye color (Blue, Green, Brown).