Welcome to Stats Made Easy 

'The numbers have no way of speaking for themselves. We speak for them. We imbue them with meaning'

Nate Silver, The Signal and the Noise

This webpage aims to teach you the basic statistical concepts and quantitative data analysis tools that will allow you to make sense of large quantitative datasets. 

We have simplified the learning material and no maths is involved to learn this material. There will be no complicated equations. After all, the computer does these calculations for you. We will teach you the underlying ideas concepts and ideas - so that you can select the right test and interpret the data correctly. 

There are many programs to analyse your data. At the moment we will introduce you to a software called Jamovi. This is a relatively simple and easy program to use. It is also open-source, so you can download it for free here. In the future, we hope to add learning materials for Python and R. 

The site includes step-by-step guides and videos for many of the t-tests you will need to analyse your data.

This website provides learning materials and guides and will link to other openly available resources where necessary.   

Course Outline

The Website set-up

Learning the underlying statistical concepts is important - don't worry no math is involved. To start your journey work through each of Stats tutorial below. Each tutorial will introduce you to the relevant key concepts and ideas using videos and step-by-step guides.  There will be links to supplementary reading and other relevant learning materials. 

The following tutorials are currently available under the menu tab on your top left:

Each tutorial also has some sub-pages, these will provide you with step-by-step instructions on how to set up and/or run a test in Jamovi. These guides will be supplemented by videos. Where possible we will use examples and provide a sample hypothesis. 

Suggested Readings

Useful Dataset


If you have any questions about the materials please email Joshua Skoczylis and we will add additional information either to the material or add a blog post on the topic.