Statistics is important for everyone. We use it every day when we digest the news. When we look at the housing market. When we try to work out what to do with all the data we generate.
Many people have built up a fear of statistics (and maths more generally), maybe because they had a bad experience of them in school. Often this is just because stats wasn’t taught in a way that worked for them.
But you CAN learn statistics! You don’t need to be able to do advanced techniques like structural equation modelling straight away, but you can know the difference between a mean and a median, or understand probability better. And it’s the foundation of Data Science, which is a very useful set of skills these days that we’ll be exploring in more depth a bit later.
Statistics is made up of two main types of methods: descriptive and inferential. Descriptive statistics helps you describe and summarise the data you have to better understand it. Inferential statistics, on the other hand, helps you to take the numbers you have and draw extended conclusions from them – for example, what a survey of a small number of people in a city says about all the people in that city.
This terrific free course from Udacity teaches you what you need to know to learn descriptive statistics. An understanding of descriptive stats is essential to moving on to inferential statistics, and this course is a great way to bed down those core concepts first.
Statistics is bread and butter for edX, and so they have a number of courses from big name universities available. This course is part of the MITx “MicroMasters” program in Statistics and Data Science, but is also just a great introduction to stats on its own.
This curriculum for beginners from the Khan Academy is made up of 16 units that cover everything from creating a bar chart to regression techniques.
Danielle Navarro has written a book that is a complete course of statistics that also teaches you how to use the free stats program R. Like a lot of stats courses out there it’s taught by a psychology researcher, so many of the examples come from behavioural science.
The Analysis Factor is a subscription service for intermediate to advanced users. Aside from workshops and mentoring they also have a blog, a newsletter and host regular free webinars on particular methods and topics, like Principal Component Analysis or Effect Size Statistics.