# Top 5 Statistics Books For A Data Scientist in 2022

Filed Under: Random

Every data has its own story. Projects fail, and sometimes won’t even start due to lack of data. But, it’s not a lack of data, but a lack of statistical knowledge which is drowning them. I wish to start this article with a quote by Andrew Lang before we go into the list of top 5 statistical books for a data scientist in 2022. With this quote, you will understand how people are using statistics to solve real-world problems.

## Top 5 Statistics Books For Budding Data Scientists

Let’s look at some of the best books that I’ve come across in my journey as a data scientist. You can choose the one that you like best and to begin with.

### 1. Practical Statistics for Data Science

Level: Beginner

Author/s: Perter Bruce and Andrew Bruce

Key points –

• This book by Peter and Andrew Bruce covers all the major topics of statistics used in Data Science. It is beginner-friendly. Anyone can grab this and start learning.
• It includes hundreds of coding examples about statistics usingÂ R programming.Â (R lovers should not miss this book :P)
• Along with reading if you want to practice stats for data science, it is the go-to book for you.
• https://github.com/andrewgbruce/statistics-for-data-scientistsÂ – You can find all the coding examples here.
• For R programmers, this is Gold.
Sale

### 2. Think Stats

Level: Python Beginner

Author/s: Allen B. Downey

Key points –

• Think stats is an awesome book that I personally prefer for python programmers who want to learn stats for data science.
• As stated in the book’s introduction, this book is all aboutÂ “Turning knowledge into Data”.
• Some of the key concepts covered in this book are statistical thinking, Hypothesis testing, correlation, and data distributions.
• Since this book entirely focuses on stats for data science, any data scientist will find this easy to follow and implement the concepts.
• Again, this book also includes many coding examples in Python.
• It shed enough light on Probability concepts such asÂ the Bayes theorem and Binomial distribution.Â
• You can get all the coding assignments here –Â https://github.com/sujitpal/thinkstats-examples.
Sale

### 3. Naked Statistics

Author/s: Charles Wheelan (Naked Economics)

Key points –

• This book is crowned asÂ “Statistics come Alive”.
• Unlike other books which are specifically focused on stats for data science, this book covers advanced statistical topics such as Central limit theorem, Regression analysis, Inference, and Evaluation as well.
• This is much like a traditional and powerful stats book, which doesn’t include any coding examples.
• But all the topics are explained with relevant examples and illustrations.
• You will get to see some of the exciting problem statements and case studies as well.
• All I can say is –Â “This never gets old”.
Sale

Level: Beginner

Author/s: Dawn Griffiths

Key points –

• One of the first and best things about this book is – All the concepts are explained in a storytelling manner, which is awesome :P.
• This book is best suited for beginners who are interested in statistics and want to learn creatively.
• I can promise you one thing –Â “You won’t get bored with this”.Â
• Some of the key concepts covered in this book are descriptive and inferential stats along with Probabilistic distributions.
• In this book, all the topics are explained with real-world examples which stand out from others.
Sale

## 5. Statistics Done Wrong

Author/s – Alex Reinhart

Key points –

• I would say this is aÂ “Lost Treasure”.Â
• Only a few people know about this book and read it. Unlike other statistics books, this deep dive into core stats concepts such as significance, Models, Errors, and Pseudoreplication.
• When I was looking for some core stats book on the web, I found this. All the concepts are clearly explained considering this is an advanced-level book.
• But make sure, you know the basic stats before you start reading it.
• This book is popular for many unique concepts which you will enjoy a lot. There is one dedicated chapter about modeling, modeling bias, and evaluation. Should get a place in top statistical books.
Sale

## Statistics books – What’s Next?

This list of top 5 statistics books can really educate you enough to get this done in your domain of work. If you are a data scientist or analyst, nothing can be best than these books. I have curated this list based on people’s opinions, concepts, flexibility, and personal experience as well. I hope you will find this useful and let’s start looking at data with a stats lens. Remember – “No data is short, but misinterpreted”. That’s all for now. Happy Stats!!!