In this lesson, we’ll explore a few different types and kinds of data. We’ll also talk about how these different types form a hierarchy, depending on how much information each provides.

Let’s look at four common types of data that you might see in data sets:

1. String

   String simply means text. We often find databases that consist of text fields. Text fields are not very easy to analyse in a dataset because we cannot easily perform calculations on them.

2. Dates

   We often keep track of the dates and times that things happen and they can come in many different formats. In tools like Excel, we can actually change those formats around to work for us in a way that looks nice. At the end of our course, we’re going to get a chance to use date data to make projections into the future.

3. Numeric

   Numeric data is the most common data that we come across in data sets. This represents numbers or quantities of things and it is common to be counting things all the time. This will be the central part of our data analysis because we can do all kinds of statistical analyses on these.

   It is important to note that we sometimes use numbers to represent categories. For example, when representing gender, we could use numbers to code these such as a 1, 2 or 3, instead of using male, female or other.

4. Currency

   This is a very common data type in statistics because we often have costs involved with the data we are representing.

Join the discussion

Why do you think it’s important to categorise our data based on the type of data that is being represented?

Use the discussion section below and let us know your thoughts. Try to respond to at least one other post and once you’re happy with your contribution, click the Mark as Complete button to check the Step off, then you can move to the next step.