Understanding data types
Before discussing data distributions, it would be useful to understand the types of data. Understanding data types is critical because the type of data determines what kind of analysis can be used since the type of data determines what operations can be used with the data (this will become clearer through the examples in this chapter). There are four distinct types of data:
- Nominal data
- Ordinal data
- Interval data
- Ratio data
These types of data can also be grouped into two sets. The first two types of data (nominal and ordinal) are qualitative data, generally non-numeric categories. The last two types of data (interval and ratio) are quantitative data, generally numeric values.
Let’s start with nominal data.
Nominal data
Nominal data is data labeled with distinct groupings. As an example, take machines in a sign factory. It is common for factories to source machines from different suppliers, which would also have different...
