---
title: "Frequency distribution"
method_id: SM.DSC.FRQ.UNIV.FREQ
family: Descriptive
version: 1.2.0
date_modified: 2026-06-18
canonical: https://clarus.ofrencber.com/library/frequency_distribution.md
source: Clarus method library
---

# Frequency distribution

> A classical statistical method in the Clarus library (Descriptive family).
> Clarus selects, assumption-checks and runs this method on your data with a
> deterministic rule engine and real numerical libraries (scipy / statsmodels);
> it never generates numbers, citations or results.

**Also known as:** frequency table; one-way frequencies; count table; tally.

## Hypotheses

- **Null (H0):** {'status': 'not_applicable', 'reason': 'Frequency distribution is a descriptive tabulation; it states no null hypothesis and performs no inferential test.'}
- **Alternative (H1):** {'status': 'not_applicable', 'reason': 'Frequency distribution is a descriptive tabulation; it states no alternative hypothesis and performs no inferential test.'}

## When to use it

Use this method when your goal is to:
- summarize one categorical variable
- tabulate counts and percentages
- describe distribution of a nominal or ordinal variable

## Data it expects

- **dependent:** 1 categorical (nominal or ordinal)
- **independent:** none
- **pairing:** none

## Assumptions

_not applicable._ A frequency distribution is a deterministic tabulation of observed counts; it makes no distributional assumptions (no normality, variance-homogeneity, or independence gate applies).

## Honest limitations

- Percentages summarize this sample only; generalizing to a population requires an explicit sampling/representativeness argument.
- A frequency table describes — it does not test. Differences between category counts are not 'significant' here; that needs a goodness-of-fit or association test.
- With many distinct categories the table becomes long and hard to read; consider collapsing categories or plotting.
- Decide deliberately whether percentages are over all cases or over valid (non-missing) cases — the two can differ when missingness is non-trivial.

## Primary sources

- Tukey, J. W. (1977). Exploratory Data Analysis. Addison-Wesley.
- Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed.). Sage. Ch. 1-2 (frequency tables and distributions).
- Agresti, A. (2018). Statistical Methods for the Social Sciences (5th ed.). Pearson. Ch. 3 (descriptive statistics for categorical variables).

## How to cite this

To cite this Clarus method page (the page itself — for the method's own primary sources, see above):

**Plain text**

Clarus, "Frequency distribution", version 1.2.0, Clarus method library, 2026. https://clarus.ofrencber.com/library/frequency_distribution.md

**APA**

Clarus. (2026). Frequency distribution (Version 1.2.0) [Statistical method, Clarus method library]. Retrieved from https://clarus.ofrencber.com/library/frequency_distribution.md

**BibTeX**

```bibtex
@misc{clarus-frequency-distribution,
  author       = {Clarus},
  title        = {Frequency distribution},
  howpublished = {Clarus method library},
  version      = {1.2.0},
  year         = {2026},
  url          = {https://clarus.ofrencber.com/library/frequency_distribution.md}
}
```

_No DOI is minted for Clarus method pages yet; this citation uses the canonical URL, version and date. Cite the primary sources above for the method's scientific provenance._

---

METHOD SM.DSC.FRQ.UNIV.FREQ · VERSION 1.2.0 · UPDATED 2026-06-18 · SOURCE Clarus method library