Agenda

Get complete understanding of Data types and their scales in Statistics/Math with easy to understand examples.

Data type is a simple but very important topic as this forms the foundation of data analysis and hypothesis testing. You go through this module and I promise that you will not face any problem in identifying data types in your future data analysis work.

We will cover following items in this module:

Please don’t get confused with scales and data types, first we will understand what are the different types of data. Once we have clarity on this, we will check 4 types of widely used scales for these data types.

Types of Data

There are three types of data, discrete, continuous and locational data. In our data analysis we mostly use continuous and discrete type of data. When we plan to apply any particular analysis to test a hypothesis, we have to first make sure that required data types are available. Basically application of any analysis type is linked with type of data, we have to first understand the type of data points available. If our data is discrete then we cannot apply some of the analysis types which work with continuous data only(Please refer to Fig-2).

Data is objective information that everyone can agree on



What we measure is not the object but some characteristic of it

Basically we use two types of data in our statistical analysis:

1.Discrete Data

2.Continuous Data

Below table illustrates how data type determines which statistical test can be applied in a given scenario. For example, if Y (dependent variable) is continuous and Xs (independent variables) are discrete then we can use ANOVA to test means. If both Y and Xs are continuous then Regression can be used.

So, it becomes very important for us to know the types of data before we move into statistics, data science, marketing research or related field.

Data Type I – Discrete Data Type

Discrete Data

Discrete data can only be integers as it is count data, for example 2, 40, 41 etc. Counted data or attribute data are answers to questions like “how many”, “how often”, “pass/fail count”.