# Ordinal vs Ordinal paired

## Part 1: Impression

With paired ordinal variables we are interested to know if there is a difference in the overall distribution. To get a first impression we could generate a cross table showing the total frequencies in each ordinal variable for each category. For example we might be interested if there is a difference in opinion on a brand *before* seeing the commercial and *after*.

Table 1

*Sample results before and after seeing commercial *

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

**with SPSS**

**with R**

**with Excel**

With Excel it shouldn't be too difficult to adjust the instructions shown in the video below to be used with paired data.

Upon inspection of Table 1 we can see that for the *before* the opinions seems to be spread out across the five categories, but for *after* the first category (fully dislike) seems to have a high percentage.

We could also check where the middle is for each variable, i.e. the value (category) for which 50% of the cases (respondents) had a score equal or higher, and 50% of the cases (respondents) had a score equal or less to.

In the example the median for *before* was 3, which corresponded to the category 'neutral', while for the *after* it was 2, which corresponded to the category 'Dislike'. This seems to confirm what we also noticed from the table itself.

**Click here to see how to determine the median with SPSS.**

**with SPSS**

Three different methods are shown below, each will eventually give the same result.

*using Frequencies*

The video below shows how to obtain the median using the Frequencies option.

*using Explore*

The video below shows how to obtain the median using the Explore option.

*using a shortcut*

The video below shows how to obtain the median using a shortcut.

Perhaps a visualisation might help here as well, which will be discussed on the next page.

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