Correlation is not causation
With this book you will:
- Discover how to test for the five correlation-causation pitfalls that even the pros fall into.
- Learn to create data analysis strategies.
- Interpret the results in a way that is easy to understand.
Best of all:
- No technical or statistical jargon – it is written in plain English.
- Packed with visually intuitive examples and makes no assumptions about your previous experience with correlations.
- Perfect for beginners!
You know it and I know it...
and yet we are constantly having to be reminded of it because we can’t seem to help but get it wrong.
How many times have you heard someone really smart say something like ‘wow, this correlation has a p-value of 0.000001 so A must be causing B…’?
It’s not our fault though – we’re only human. We seek explanation for patterns and events that happen around us, and if something defies logic, we try to find a reason why it might make sense. If something doesn’t add up, we make it up.
OK, so if correlation does not necessarily imply causation, there must be a reason for that, and there must be something that is causing what we observe.
That is what this book is all about.
Why should you care what I say?
I have worked with data for most of my adult life. I have worked with data from the Visible Human Project, the Human Genome Project, a major European Soil Database, Medical Imaging Data, and loads and loads of Data from Clinical Studies Research.
I now help other scientists and business analysts just like you get the story of their data quickly and easily.
“My Mission Is To Unleash Your Inner Data Ninja”
CORRELATION IS NOT CAUSATION
This book explains how to systematically test for the five most common correlation-causation pitfalls that even the pros fall into (occasionally).
Learn to create strategies to analyse the data and interpret the results in a way that is easy to understand.
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