Statistical data types | Economipedia

The types of statistical data is the classification that is made about the data used in statistics. This classification is very important since, depending on the type of data with which one works, some statistical techniques or others can be used.

That is, the types of statistical data are categories that allow separating information with different characteristics. This distinction is relevant so that researchers know how to carry out the analysis.

Before explaining what types of statistical data exist, it is important to keep in mind the concept of data. Data is the representation of statistical variables through the assignment of a value, letters or symbols.

The data are essential to be able to make statistical inference. Statistical inference is the set of methods that allow drawing conclusions about a population of data from a sample.

Therefore, a piece of data provides us with specific information about a statistical variable. In order to work with them, it is necessary to classify and order them in the correct way.

Below we detail the different types of statistical data that there are:

• Qualitative: This type of data is not quantifiable and can be expressed both in words and in numbers. They refer to characteristics of what is being studied. They can be classified in turn into:
• Nominals: Nominal data are those that express with a name a quality that does not have to be sortable.
• Ordinals: They express a quality through data that can be ordered through a previously defined scale.
• Quantitative: These data are expressed in numbers and they can be measured. They can be in turn:
• Discreet: The values ​​that they can take are given between finite intervals of data. That is to say, the options of this type of data are limited to a series of values ​​(Let’s think about the whole numbers).
• Continuous: This data is extracted from a totally infinite range of values, so the number of different data that can be obtained is unlimited.