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Binary vs. Binary (unpaired/independent)

Introduction

When you have a two binary variables you might be interested if there is an association (relation) between the two. For example if the gender (male/female) has an influence on where students had their secondary school (The Netherlands, or somewhere else).The analysis breaks down into the following parts (for each part in this analysis a separate page was created):

Part 1: Descriptive analysis
Use descriptive statistics to get an impression of the data, using:

1. A cross table of the two variables
2. A visualisation of the data with a clustered bar chart

Part 2: Inferential statistics
After the first impression determine what can be said about the population based on your sample data by:

1. Determine if there is a significant association using a Fisher Exact test
2. determine the effect sizes (Odds Ratio)

Part 3: Reporting
As the last step, you will need to write up all the results.

Let's begin with getting an impression of the results in the first part.

Binary vs. Binary

Introduction

Impression

Visualisation

Test

Effect Size

Reporting

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