Important: It looks like you are browsing from a non-Windows device. Please be aware that Analyse-it is only available for Microsoft Windows.
Training and consultancy for Analyse-it Read the blog post

# Contingency tables

Contingency analysis describes and visualizes the distribution of categorical variables, and makes inferences about the equality of proportions, independence of the variables, or agreement between variables.

**Contingency table**

A contingency table, also known as a cross-classification table, describes the relationships between two or more categorical variables.**Grouped frequency plot**

A grouped or stacked frequency plot shows the joint or conditional distributions.**Effect size**

An effect size estimates the magnitude of the difference of proportions or the association between two categorical variables.**Relative risk**

Relative risk is the ratio of the probability of the event occurring in one group versus another group.**Inferences about equality of proportions**

Inferences about the proportions in populations are made using random samples of data drawn from each population of interest.**Inferences about independence**

Inferences about the independence between categorical variables are made using a random bivariate sample of data drawn from the population of interest.**Mosaic plot**

A mosaic plot is a visual representation of the association between two variables.

**Available in Analyse-it Editions**

Standard edition

Method Validation edition

Quality Control & Improvement edition

Ultimate edition

- What is Analyse-it?
- Administrator's Guide
- User's Guide
- Statistical Reference Guide
- Distribution
- Compare groups
- Compare pairs
- Contingency tables
- Contingency table
- Creating a contingency table
- Creating a contingency table (related data)
- Grouped frequency plot
- Effect size
- Estimators
- Estimating the odds ratio
- Estimating the odds ratio (related data)
- Relative risk
- Inferences about equality of proportions
- Inferences about independence
- Mosaic plot
- Creating a mosaic plot
- Study design
- Correlation and association
- Principal component analysis (PCA)
- Factor analysis (FA)
- Item reliability
- Fit model
- Method comparison
- Measurement systems analysis (MSA)
- Reference interval
- Diagnostic performance
- Control charts
- Process capability
- Pareto analysis
- Study Designs
- Bibliography

Version 5.30

Published 15-Apr-2019