# Analysing a nominal and scale variable

## Part 2: Visualisation

To visualise the sample data between a nominal and a scale variable various options exist, but two commonly used ones are a side-by-side box plot and a split histogram. For each of these options something can be said. The **side-by-side box plot** is a visualisation of some descriptive measurements, and therefor a bit more technical. A downside of a **split histogram** is that it becomes perhaps too large if you have a lot of different categories in the nominal variable.

For the example used on the previous page, I'll use a split histogram such as the one shown in Figure 1.

*Figure 1*. Location vs Grade for course.

**Click here to see how to create a split histogram with SPSS, R (Studio), Excel (somewhat), or Python.**

**with SPSS**

**with R (Studio)**

**with Excel (somewhat)**

Unfortunately it is not possible (to my knowledge) to create a singele chart that shows a split histogram, however you could mimic the result by showing three different histograms and place them underneath each other.

**with Python**

The number of bars (bins) can change the look of this. There are various formal rules on how many bars there should be, and even more rule of thumbs. I recommend using between 5 and 12 bars. In this example I've used 8.

When looking at the histograms you can look at the general shape, where the peak is for each and if there might be some unusual scores. From Figure 1 we see the same things as we already established from the descriptive statistics. In the report I recommend using a ‘Introduce – Show – Tell’ approach. So when reporting this graph, it could be for example like this:

A question of interest was how do students grade the course across the three locations. Students could give the course a grade from 0 (low) to 100 (high). The results are shown in Figure 1.
As can be seen Figure 1 the students in gave the course a higher grade than those in Haarlem and Rotterdam. The variation in Rotterdam was very high. |

Now that we have a good impression from the sample data, we can move on to see what this sais about the population, which will be the topic for the next page.

As mentioned earlier an alternative visualisation is to use a box-plot

**Click here to see how to create a boxplot with SPSS, with R, or with Excel**

**with SPSS**

**with R (Studio)**

**with Excel**

## Excel (prior to 2016 (no video))

For earlier versions of Excel read the instructions on this site (opens in new tab).

## Excel 2016

## Excel 2019

**Nominal vs Scale**

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