Friday, January 8, 2021

PyATL Bytecode: Review of Bayesian Statistics the Fun Way

This is the kind of book you would hand to someone to bring statistics down to earth for them, making it easy without a lot of math. While people who are already familiar with Bayes or statistics might not get much out of this book, it is perfect for someone who knows nothing about them. While some of the topics I didn’t consider personally fun, I would say that this author did a great job making statistics less scary and less boring. I think this would be perfect for an introduction to statistics class or just to read in your own time if you want to increase your knowledge of Bayes algorithms. If you’ll enjoy that then jump on into “Bayesian Statistics the Fun Way”

Ok, are they gone? I think I got rid of all the people who will only look at the highlight sentences. So now I’m going to sit down and go through all the actual pieces of this book and explain my system. I rated this book on 3 main subjects:

Readability: How easy is this book to read and how quickly could a person finish the whole book

Accuracy: how accurate is the book? How many errors does it make in the code or text?

Subject: Does this book do what the cover or back says it does? Is what the book wants to teach you good?

Bonus Points: This is just for outside resources that the book points to directly. I might also add some places where you can find more education from the author such as informative twitter threads or medium articles that the author offers for free.

Readability 5/10:
This book can be fun at times and it does go a long way to make statistics and math something that the average person can get into. The problem with this book is the subject will only allow it to take this so far. You will probably find yourself getting through the first few chapters easily. Taking the book and reading it pieces at a time will actually be a nice and relaxing way to educate yourself on statistics.
The problem is that you will eventually get to more complicated sections and, if you try to read this quickly or in a single sitting, you will find finishing this book difficult. I read this book over 3 weeks at about 10-15 pages per day. This book is best enjoyed in bites or nibbles rather than a full gulp of a read. I think this is a positive for the book itself and allows any reader who might not fully grasp the material time to digest and ask questions.

Accuracy 10/10:
What can I say other than this book hits it’s mark? This is a technical book for the average person and because of that I couldn’t find anything that really stuck out as debatable or incorrect.

Subject 10/10:
This is the kind of book that someone wrote because they didn’t want the next person to get the same dry education that they got back in college. While this doesn’t mean that the subject is fun in it’s own right, the author does a great job to make it far more palatable than this subject could ever be in most classroom text books. If you’re going to be teaching Bayes in a computer science course or in a statistics class before you move onto something like Kmeans, then this would be the book to teach with. Even first year students without heavy mathematical knowledge will be able to pick it up and stroll through on their own. The funny thing about this book is, while reading the first few chapters, the only thing I could think was “There are some conspiracy theorists out there who could improve their lives and remove their theories with this book.” While I’m hesitant to say “This is a book for conspiracy theorists!” I would say that it will do something to improve your reasoning on the world around you. So if you know a friend who is drifting to close to the crazy then see what throwing this book at them will do.

Bonus points:
+1 To the sections at the back teaching R and Calculus:
I would like to give a shout out to the author who is willing to make a book that the average person can understand, but still put in a section to “Know More.” This is just a tip of the hat as I have seen a lot of authors come into these subjects with the idea of “You don’t need this for my book so I won’t even give you a hint about it. You’ll get that in someone else’s book.” The section is appreciated

About the Author:
After researching the author a little bit, it seems that he has a website where he blogs about data science topics and his next book. He has points where you can get involved and ask him questions directly. So if you enjoyed this book and want to step deeper in then I would recommend googling Will Kurt and hopping into what you find. Who knows you might ask a question that will change his next book.



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