# Nominal vs. Nominal

## Part 1: Impression of the sample data (cross table)

To begin analysing a potential association between two nominal variables, we can start by getting an impression from the sample data using a so-called **cross table**, or also known as a **contingency table**.

For example, I might be interested to know if gender has an association with the marital status, and generate the following cross table from my sample.

**Click here to see how you can create a cross table as above, with SPSS, with R, or with Excel.**

**with SPSS**

There are a two different ways to create a cross table with SPSS.

*using Crosstabs*

*using Custom Tables*

**with R**

**with Excel**

Note that in the example the column totals add up to 100% each, which makes it easy to compare the results between the two genders. Depending on your results you might prefer to set each row as 100% or even based on the grand total.

Looking at the percentages in the example cross table, it seems that most percentages are similar with the biggest difference between Male and Female at widowed.

Rather than using a cross table we might want to visualise the results, which will be discussed on the next page.

**Two nominal variables**

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