Nominal

Nominal refers to a level of measurement that categorizes data into distinct groups, without any order or priority. It is often used in research to classify and categorize data. Examples of nominal data include gender, race, religion, and political affiliation.

Definition[edit | edit source]

Nominal is derived from the Latin nomen, meaning "name". In statistics, a nominal scale is used for labeling variables, without any quantitative value. Unlike ordinal, interval, and ratio scales, a nominal scale does not imply any sort of order among the values.

Characteristics[edit | edit source]

Nominal data has the following characteristics:

It is qualitative: Nominal data is non-numeric and is categorized based on attributes, characteristics, or properties.
It is mutually exclusive: Each data point can only belong to one category.
It is exhaustive: All possible categories are included, so every data point has a place.
It has no order or direction: The categories can be rearranged without affecting the meaning of the data.

Uses[edit | edit source]

Nominal data is used in a variety of fields, including medicine, sociology, psychology, and business. It is particularly useful in research where data can be observed but not measured, such as studies on race, religion, or gender.

Analysis[edit | edit source]

Analyzing nominal data often involves counting the number of data points in each category and calculating the percentage or frequency of each. Common statistical tests used with nominal data include the Chi-square test and Fisher's exact test.

References[edit | edit source]

Nominal Resources
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