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.
Most people use statistics like a drunk man uses a lamppost; more for support than illumination.
-Andrew Lang.
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
You can download the PDF version for this book using above download button.
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 using R programming. (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-scientists – You can find all the coding examples here.
- For R programmers, this is Gold.
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 about “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 as the Bayes theorem and Binomial distribution.Â
- You can get all the coding assignments here –Â https://github.com/sujitpal/thinkstats-examples.
3. Naked Statistics
Level: Advanced
Author/s: Charles Wheelan (Naked Economics)
Key points –
- This book is crowned as “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”.
4. Head-First Statistics
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.
5. Statistics Done Wrong
Level – Advanced
Author/s – Alex Reinhart
Key points –
- I would say this is a “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.
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!!!
More read: Why learn Statistics?