Lies, Damned Lies, and Statistics
We are exposed to the use of statistics in everyday life, but it is quite easy to fall victim of statistical fallacies. This talk will help you recognise these fallacies, so you can protect yourself from the misuse of statistics, ultimately becoming a better citizen.
Statistics show that eating ice cream causes death by drowning. If this sounds baffling, this talk will help you to understand correlation, bias, statistical significance and other statistical techniques that are commonly (mis)used to support an argument that leads, by accident or on purpose, to drawing the wrong conclusions.
The casual observer is exposed to the use of statistics and probability in everyday life, but it is extremely easy to fall victim of a statistical fallacy, even for professional users. The purpose of this talk is to help the audience understand how to recognise and avoid these fallacies, by combining an introduction to statistics with examples of lies and damned lies, in a way that is approachable for beginners.
Agenda: -Correlation and causation -Simpson’s Paradox -Sampling bias and polluted surveys -Data visualisation gone wild -Statistical significance (and Data dredging a.k.a. p-hacking)
Marco Bonzanini is a freelance Data Scientist based in London, UK. Co-organiser of the PyData London meet-up and co-chair of the PyData London 2018-19 conference. Python publications: Mastering Social Media Mining with Python (book, PacktPub, 2016) Data Analysis with Python (video course, PacktPub, 2017) Practical Python Data Science Techniques (video course, PacktPub, 2017)