Chapter 3 Descriptive statistics (Module 5)

Descriptive statistics, as the name implies, are used to describe data. A key part of the quantitative research process is understanding the various ins and outs of your data. You’ll probably have a sense of why this is important if you have the qualitative presentation still fresh in your mind - namely, knowing your data is also really important for knowing what to do with it.

In this first module, we will start with the first steps of understanding quantitative data. This involves visualising our data to see what it looks like, and describing key features of the data. If you’re familiar with statistics then some of this may seem a bit trivial, but it’s important that we get the basics right before we go on to doing fancy statistical tests.

Also, I know that the idea of doing statistics and maths freaks a lot of us out - and that’s totally normal. Yes, there will be some number-crunching and maths in the next series of modules, but the focus of these modules is not to force you to calculate things by hand. You will encounter a whole bunch of mathematical formulae, but the point of doing so is to illustrate the concepts that underpin them. These concepts are crucial to understanding the ‘magic’ that happens with quantitative analysis, and a really solid foundation in statistical concepts will go a long way.

That being said, throughout these statistics modules there will be a number of activities that ask you to actively work with sample datasets and analyse them. We promise that you will get so much more out of these modules if you complete these activities, because readings and webpages aren’t the best substitute for actually doing it and getting your hands dirty with data.

By the end of this module you should be able to:

• Create both appropriate and meaningful graphs from data
• Calculate various forms of descriptive statistics
• Interpret both graphs and descriptive statistics, and explain what they tell you

Figure 3.1: xkcd: Statistics