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!

19 Essential Tips to Scrub Your Dirty Data

Data cleaning is a waste of time.

If the data had been collected properly in the first place there wouldn’t be any cleaning to do, and you wouldn’t now be faced with the prospect of weeks of cleaning to get your dataset analysis-ready.

But it doesn’t have to be so difficult. If you're organised and follow a few simple rules your data cleaning processes can be simple, fast and effective.

Practical Data Cleaning (now in its 5th Edition!) explains the 19 most important tips about data cleaning with a focus on understanding your data, how to work with it, choose the right ways to analyse it, select the correct tools and how to interpret the results to get your data clean in double quick time.

Best of all, there is no technical jargon – it is written in plain English and is perfect for beginners!

Associations and correlations are ways of describing how a pair of variables change together as a result of their connection. In other words, if one of your variables changes, the other is likely to change too.

These types of analysis are some of the most used – and misunderstood – statistical techniques. Most results you’ll encounter are wrong, and for a very good reason. In this book we’re going to understand just why this is, avoid the most common pit-falls and learn how to make sure you get the correct results first time, every time.

Here, you’ll learn a holistic method of discovering the story of all the relationships in your data by guiding you through a variety of the most used association and correlation tests – and helping you to choose them correctly.

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.

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!