Nominal Data
Nominal data is a type of categorical data that is qualitative in nature. Labels and tags that do not possess any numerical properties are used to classify nominal data. Grouping of nominal data is done with the help of a nominal variable and there is no intrinsic ordering within these groups.
Nominal data can be analyzed using non-parametric statistical tests such as the Chi-Squared test and Cochran Q's test. In this article, we will learn more about nominal data, its analysis, characteristics and see various associated examples.
| 1. | What is Nominal Data? |
| 2. | Nominal Data Characteristics |
| 3. | Nominal Data Analysis |
| 4. | Nominal Data Examples |
| 5. | Nominal Data vs Ordinal Data |
| 6. | FAQs on Nominal Data |
What is Nominal Data?
Nominal data and ordinal data are the two types of categorical data. Categorical data is qualitative in nature as logical and arithmetic operations cannot be performed on such data. Non-parametric statistics is used in the analysis of ordinal and nominal data as they are categorical in nature. Other types of data include ratio and interval data that are quantitative in nature.
Nominal Data Defintion
Nominal data can be defined as a type of data that can be divided into mutually exclusive groups that do not overlap using labels and tags. These tags could be numerical in nature but do not possess any quantitative properties. Furthermore, nominal data cannot be ranked or ordered.
Nominal Data Characteristics
The most important characteristics of nominal data are given as follows:
- Nominal data is qualitative in nature.
- Groups of nominal data are mutually exclusive and these categories do not overlap with each other.
- Descriptive tags and labels are used to categorize nominal data.
- Nominal data is not quantitative in nature thus, arithmetic and logical operations cannot be performed.
- Nominal data has a mode but does not have a mean or median.
- A definite order cannot be assigned to nominal data. In other words, such data cannot be ranked or data.
- Graphs and charts are used to visualize nominal data.
Nominal Data Analysis
Nominal data cannot be analyzed using parametric statistics as it does not possess any quantitative property. One way of analyzing nominal data is by dividing it into different categories using nominal variables. The mode, frequency, and percentage can be calculated for such groups and the results can be displayed in the form of graphs.
Another way of analyzing nominal data is by using certain hypothesis testing. Tests such as the Chi-squared test, Cochran's Q test, Fisher's Exact test, and McNemar test can be used to make inferences about the population data.
Nominal Data Graph
A bar graph and a pie chart are the most common ways of representing nominal data. Suppose a survey was conducted. Participants were required to choose which fruits they liked among apples, oranges, and bananas. The frequency distribution table for this nominal data is given as follows:
| Fruits | Frequency | Percentage |
|---|---|---|
| Apples | 13 | 48.1% |
| Oranges | 9 | 33.3% |
| Bananas | 5 | 18.5% |
The bar graph and pie chart for this nominal data can be given as follows:
Nominal Data Examples
Nominal data can be expressed in words or numbers however, they cannot be ordered and they do not have any numerical properties. Given below are a few examples of nominal data.
- Hair Colour - Black, brown, blonde, red, silver.
- Pin code - 482001, 400056, 49375
- Test Status - Pass, Fail
- Movie Genres - Comedy, musical, horror, drama, satire
Nominal Data vs Ordinal Data
Categorical data can be divided into both nominal data and ordinal data. The table given below lists the difference between nominal data and ordinal data.
| Basis | Nominal Data | Ordinal Data |
|---|---|---|
| Definition | Nominal data can be defined as categorical data that cannot be ranked or ordered. | Ordinal data is also categorical data but it possesses intrinsic ordering |
| Hypothesis Tests | Chi-squared test, Cochran's Q test, Fisher's Exact test, and McNemar test are used. | Wilcoxon signed-rank test, Wilcoxon rank-sum test, Friedman 2-way ANOVA, and Kruskal-Wallis 1-way test are used for hypothesis testing. |
| Data Analysis | Nominal data can be categorized into groups that can be represented using frequency distributions and graphs (bar graph, pie chart, etc.) | Mode, median, quartiles, percentiles, etc., can be determined for analyzing ordinal data. |
| Data Collection Techniques | Nominal data can be collected using open-ended and closed-ended questions, as well as multiple-choice surveys. | Ordinal data can be collected using surveys that provide a rating scale. |
| Advantage | Nominal data lets the participants express their views freely. | Ordinal eliminates irrelevant data and gives a more precise result |
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Important Notes on Nominal Data
- Nominal data is a type of categorical data that does not possess any intrinsic ordering.
- Nominal data is qualitative in nature.
- Bar graphs and pie charts can be used to represent nominal data.
- Nominal data can be analyzed using non-parametric statistical tests such as the Chi-squared test.
Examples on Nominal Data
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Example 3: Use a pie chart to represent the following nominal data.
Pets Owned Frequency Dogs 48 Cats 32 Fish 12 Snakes 6 Solution:
Pets Owned Frequency Percentage Dogs 48 48.9% Cats 32 32.6% Fish 12 12.2% Snakes 6 6.1% 
FAQs on Nominal Data
What is Nominal Data in Statistics?
Nominal data in statistics can be defined as categorical data that is qualitative in nature and cannot be ordered or ranked. Thus, arithmetic and logical operations cannot be used on nominal data.
What are the Characteristics of Nominal Data?
The characteristics of nominal data are as follows:
- Nominal data groups are mutually exclusive.
- It is qualitative in nature.
- Nominal data can have a mode.
- Labels and tags are used for nominal data.
How to Represent Nominal Data?
Nominal data can be represented using bar graphs and pie charts. Frequency and percentage distribution tables can also be used to show nominal data.
What Hypothesis Tests can be Conducted on Nominal Data?
There are 4 types of hypothesis tests that can be used on nominal data. These are the Chi-squared test, Cochran's Q test, Fisher's Exact test, and McNemar test.
Can You Find the Mean of Nominal Data?
The mean of nominal data cannot be determined. This is because nominal data is not quantitative in nature and statistical computations cannot be performed on it.
How to Analyze Nominal Data?
Nominal data can be analyzed by grouping the data. The frequency and percentage can be calculated for such groups which can further be represented using graphs.
What is the Difference Between Nominal Data and Ordinal Data?
Nominal data and ordinal data are both types of categorical data. The former cannot be ranked while the latter can be intrinsically ordered.