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Trend test

As explained in Effective Data Analysis

A trend test is a chi-square test that evaluates whether category frequencies change systematically across ordered groups or time.

A trend test is a chi-square test that checks whether frequencies in a categorical variable change systematically across ordered groups or over time. section 5.2.3

It addresses pattern questions rather than simply asking whether categories differ, making it useful when group order or time provides meaningful structure. section 5.2.3

Distinguish it from related chi-square tests:

  • Goodness-of-fit tests compare one sample’s observed frequencies with expected frequencies. section 5.2.3
  • Tests of independence compare observed and expected frequencies between two categorical variables. section 5.2.3
  • Trend tests focus on systematic change across ordered groups or time. section 5.2.3

The treatment names the test’s purpose but does not provide its calculation, implementation procedure, assumptions, or a worked trend-test example. section 5.2.3

How Effective Data Analysis covers it

How deep it goes
Defines the purpose and distinguishes related tests, but stops short of methodology, calculation, and implementation.
Examples
Uses ordered groups and time as the concrete settings, without presenting a worked dataset or trend-test calculation.
What it assumes
Assumes familiarity with categorical variables, frequencies, groups, time, and the broader chi-square test family.
How it connects
Connects trend tests with chi-square tests, goodness-of-fit tests, tests of independence, and categorical variables.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Effective Data Analysis. The section links point to the parts of the book it draws on.