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By Dan Morris, 205 pages, published Oct 2, 2016
Amazon's Description:
If you’ve recently used Google search to find something, Bayes' Theorem was used to find your search results. The same is true for those recommendations on Netflix.
Hedge funds? Self-driving cars? Search and Rescue? Bayes' Theorem is used in all of the above and more.
At its core, Bayes' Theorem is a simple probability and statistics formula that has revolutionized how we understand and deal with uncertainty. If life is seen as black and white, Bayes' Theorem helps us think about the gray areas. When new evidence comes our way, it helps us update our beliefs and create a new belief.
Ready to dig in and visually explore Bayes' Theorem? Let’s go!
Over 60 hand-drawn visuals are included throughout the book to help you work through each problem as you learn by example. The beautifully hand-drawn visual illustrations are specifically designed and formatted for the kindle.
This book also includes sections not found in other books on Bayes' Rule. These include:
- A short tutorial on how to understand problem scenarios and find P(B), P(A), and P(B|A). - For many people, knowing how to approach scenarios and break them apart can be daunting. In this booklet, we provide a quick step-by-step reference on how to confidently understand scenarios.
- A few examples of how to think like a Bayesian in everyday life. Bayes' Rule might seem somewhat abstract, but it can be applied to many areas of life and help you make better decisions. Learn how Bayes can help you with critical thinking, problem-solving, and dealing with the gray areas of life.
- A concise history of Bayes' Rule. - Bayes' Theorem has a fascinating 200+ year history, and we have summed it up for you in this booklet. From its discovery in the 1700’s to its being used to break the German’s Enigma Code during World War 2.
- Fascinating real-life stories on how Bayes' formula is used everyday. From search and rescue to spam filtering and driverless cars, Bayes is used in many areas of modern day life.
- An expanded Bayes' Theorem definition, including notations, and proof section. - In this section we define core elementary Bayesian statistics terms more concretely.
- A recommended readings section. From The Theory That Would Not Die to Think Bayes: Bayesian Statistics in Python and many more, there are a number of fantastic resources we have collected for further reading.
eBook is free at time of posting. Please check price before buying.
It'd be great if everyone in Australia who considers themselves a leader could understand Bayesian Statistics…
It's obvious our politicians don't.