Probability for the Enthusiastic Beginner is a great book to learn probability and statistics in an easy way, start from a point of very little knowledge and build up to become familiar with the most common concepts on the field.
Along with Bayesian Statistics: The Fun way, this is one of the top 3 books to get started on probability that we have found, and either of them can serve as a perfect introduction to probability book.
The author develops the main concepts of probability theory from a bottom-up approach, covering things like dependent and independent events in a way which might seem obvious for most, but that is not so clear for those with no previous statistical background or that are studying the topics for the first time.
The book contains enough concepts, and is written in such a way, that it is not only interesting for those that are willing to start learning about probability, but also for those who already have a decent background in statistics and want to consolidate their knowledge. A little bit of calculus and algebra is required, but on a very superficial level: being confortable with high-school math is probably enough.
The tail of the name Probability for the Enthusiastic Beginner has the following explanation: if you want the book will serve you as an introduction to probability, and you will perfectly understand the core concepts after reading it. However, if you want to dig deeper, and learn where the various results and theorems come from, and how they are related, the book offers the materials and has the depth to do so as well.
The text is very clearly written, and includes a large number of solved problems (which we recommend to try to complete), making it a fantastic choice as a self-education text, or as a complement to an statistics or probability course.
Overall, we think this text is an awesome Introduction to probability and its surrounding elements.
The contents of the book are the following:
- Chapter 1: Combinatorics. How combinations are computed.
- Chapter 2: Probability. What probability is, Bayes Theorem and Stirling’s Formula.
- Chapter 3: Expected values, variance and standard deviation.
- Chapter 4: Various distributions; uniform, Bernuilli, binomial, exponential, Poisson and Gaussian Distribution.
- Chapter 5: Gaussian approximations, the law of large numbers and the central limit theorem.
- Chapter 6: Correlation and regression.
- Appendices: Euler’s Number, neat probability concepts, approximations, and important results.
As mentioned earlier, there are also exercises that come with the book. These exercises can be challenging, and we recommend doing them before checking the solutions that are also included.
Here you can find a link to the official website of the book.
Probability: For the Enthusiastic Beginner is one of the best books out there to get started with probability theory, with some very light previous requirements that can be learned with little effort, or that you probably already know . It provides enough material to get the reader to understand advanced statistical concepts but not so much that it might result overwhelming or heavy.
It is a book that is very easy to read, and that serves as a great text to get Into probability theory in an easy, gradual, and pedagogical manner. For us, this should be every students first book about probability ! It was a real pleasure to work through it, the reading is fluid, and you constantly feel like you are learning and making progress.
We definitely recommend it as a top read. You can find it on Amazon at the best price here:
Probability for the Enthusiastic Beginner
- Morin, David J. (Author)
- English (Publication Language)
- 371 Pages - 04/03/2016 (Publication Date) - CreateSpace Independent Publishing Platform (Publisher)
Thanks for reading How to Learn Machine Learning, and have a wonderful day!