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Now With 3 Free Bonuses!

You can now get the following FREE bonuses with this book:

Introduction to Associations and Correlations

• A free excerpt from the #1 book on Associations and Correlations

The Future of Statistics

• An anthology written with the contributions of some of the most prominent statisticians, data analysts and Data Scientists in the world to help you take the next steps in your Data Ninja journey!

Exploratory Data Analysis - The Big Picture

• An Ultra Hi-Def poster created to help you understand which statistics to use in exploratory data analysis!

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You can download the content in a zip file by going to your Leanpub library here https://leanpub.com/user_dashboard/library, selecting the book, and then clicking on the "Download Extras" download link.

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Correlation Is Not Causation.

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.

If we discover a correlation between a pair of variables there are five alternatives to one being the direct cause of the other, and we’ll unmask all five in this book.

Then, once we understand each of these alternatives, we’ll formulate a plan to discover whether we have a direct causal link or whether there is some other explanation.

Correlation Is Not Causation explains how to systematically test for the five most common correlation-causation pitfalls that even the pros fall into (occasionally). We’ll learn to create strategies to analyse the data and interpret the results in a way that is easy to understand.

Best of all, there is no technical or statistical jargon – it is written in plain English.

It is packed with visually intuitive examples and makes no assumptions about your previous experience with correlations – in short, it is perfect for beginners!

Discover the world of correlation and causation. Get this book, TODAY!