Different data require different methods of summarising, describing and analysing.

There are four main types of data: **Nominal, Ordinal, Interval** and **Ratio**. It is important to be able to identify which type of data you have in order to choose appropriate statistical methods. Take a look at the examples below for a quick refresher of the four types of data:

### Nominal

Nominal data are named variables. Nominal data is unordered, categorical and **mutually exclusive** - which means that each category is separate and cannot occur at the same time.

Examples of nominal data are:

- Different countries: Afghanistan, Brazil, China, etc.
- Yes or No answers. When a variable only takes only two values, we call this variable
**dichotomous**.

### Ordinal

Ordinal data are named variables that have a meaningful order. Ordinal data is ordered, categorical and mutually exclusive (cannot happen at the same time).

Examples of ordinal data are:

- Body Mass Index (BMI): Underweight, normal weight, overweight, obese.
- Responses to questionnaires: Strongly Disagree, Disagree, Neutral, Agree and Strongly Agree. This is known as a Likert scale, and is often coded using numbers where:

1 = Strongly Disagree

2 = Disagree

3 = Neutral

4 = Agree

5 = Strongly Agree.

How should I analyse Likert data? Take a look at the following article Analysing LIkert Scale/Type Data from Maths Support at St Andrews University for some ideas.

### Interval

Interval data is quantitative (numbered data) that has a meaningful interval between data points but does not have a meaningful zero, where zero means nothing.

Examples of interval data are:

- Temperature (in degrees Celsius, 0 degrees Celsius is cold, not no temperature)
- Size of shoes (EU size 0? This shoe size doesn’t exist.)

### Ratio

Ratio data is quantitative (numbered data) that has a meaningful interval between data points. Unlike Interval data, ratio data has a meaningful zero - known as a **true zero**.

Examples of ratio data are:

- Length (in cm, where 0 cm has no length).
- Weight (in kg, where 0 kg has no weight).