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Mastering basics, Bayes, and AI
The hardest part of stats is understanding how it all fits together. If you want a book that takes you from the very basics all the way through to the most advanced concepts, this is for you!
Minimum price
$5.00
$20.00
Buying multiple copies for your team? See below for a discount!
About the Book
An approachable, self-contained, and manageable course in statistics. Starting out with the fundamentals of statistics (e.g., how to compare averages and what a p-value is), by the end you will be able to fit advanced Bayesian models and even use neural networks to analyse images. Developed over ten years of teaching at universities in the UK, US, and Canada, this book comes with worked examples in R for you to use in your own work.
Topics covered in the chapters include:
As well as PDF and ePub versions, you will have access to (1) a password-protected online version of the book for easy copy-pasting of code, (2) a link to all datasets used in the book, and (3) laptop recordings of the author explaining the topics.
Every chapter of the book is written; I am currently adding in last pieces and giving it one final proof-read. I have used these materials for >10 years, so I'm confident of them, but I'm giving a discount now (buy for only £5!) while I'm proof-reading. Buy now and save! You will have access to updates and the finished version if you buy now.
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About the Author
I'm an Associate Professor at Imperial College London, where I lead a research group focusing on biodiversity, health, statistics, and computing. I have published >100 scientific papers on topics ranging from designing global conservation strategies, forecasting COVID dynamics, and understanding how flowers respond to climate change. I have led and contributed to numerous R packages (e.g., caper, SymbiotaR2, pez, ), which have in total been downloaded millions of times.
I have taught under- and post-graduate courses in biology, statistics, and computing for >10 years. My statistics courses are popular with students; my undergraduate students voted me the winner of the 2009 'Faculty Teaching Award' while I was a PhD student, my postgraduate students voted me 'Best Supervisor' in 2021, and I received a 'Department Teaching Award' in 2024.
When I'm not doing any of the above, I spend time with my family, a cute whippet named Coco, and two excitable gerbils named Marshmallow and Chestnut.
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