The 14 Best Statistics Books for Data Science

Statistics and data science are among the most challenging subjects to self-learn. If you have never had experience in any of these two fields, you will need to be ready to put time and commitment to learning these always-evolving disciplines. However, in this process, picking the right volumes and textbooks is essential. 

The best statistics books for Data Science include Naked Statistics: Stripping the Dread from the Data by Charles Wheelan and Practical Statistics for Data Scientists – Peter Bruce. To learn more about stats in R, read Discovering Statistics Using R – A. Field, J. Miles, and Z. Field.

Find out more about the best books to learn statistics from scratch and become a skilled data scientist.

Important Sidenote: We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and identified 6 proven steps to follow for becoming a data scientist. Read my article: ‘6 Proven Steps To Becoming a Data Scientist [Complete Guide] for in-depth findings and recommendations! – This is perhaps the most comprehensive article on the subject you will find on the internet!

Are Books Effective to Learn Statistics for Data Science?

Textbooks and specialized training sessions have been used in university courses to improve the quality of the teaching. However, if you are trying to learn statistics from scratch to become a data scientist, be aware that there are significant limitations presented by textbooks. 

• Data Science, as stated in several Forbes articles, is a relatively new field, in which innovations happen every day and developments are carried out continuously. Consequently, only a few staple books can be useful to understand the basic concepts of this discipline. Therefore, if you are looking for some recent research or innovation, you are better off consulting the internet or journals on the field. 

• If you are not sure about what data science entails, there is always the danger of getting lost in the myriad of information that composes the field of statistics. While the majority of concepts are also the pillars at the core of the field of Data Science, some other concepts might not be so relevant when you are looking for a job in data science. 

• Statistics are considered among the most challenging subjects to self-learn using only volumes and textbooks. Therefore, you will need to be well-equipped with patience, commitment, constancy, and willingness to go over some more complicated subjects a few times. 

While it is easy to get discouraged, keep in mind that it is normal to find some challenges when studying a field so complicated and in evolution like data science or statistics can be. Additionally, using other learning methods and tools such as online videos and training can help you understand some concepts easier and faster.

Statistics – Robert S. Witte and John S. Witte

If you wish to approach the field of statistics and you have no previous experience in the field, this is a suitable book for you. 

The 11th edition of this volume has been released, and you can find updated information and latest innovation alongside staple principles and concepts of statistics.

In terms of knowledge level, you can expect to grow from a beginner level to an undergraduate level. The journey is assisted by the organized chapter, easy-to-understand text, and clear graphs. 

While this book is perfect if you are just starting your studies, many professionals opt to use it as a backup reference for certain projects.

Among the most important features of this book is the fact that every jargon and obscure terms are explained in detail. Some of the concepts covered include variations of coefficient and correlation, interpretation, and hypothesis.

• Accessibility: available online, the price varies from over $170 to $21 (for the eBook)
• Experience level: Beginner
• Best for: learners interested in the basics of statistics. It focuses on basic principles and essential concepts.
• Find it here in the eBook format: Statistics, 11th Edition 

Barron’s AP Statistics, 8th Edition – Martin Sternstein, PhD

Written by the head of various math departments in Universities, the Barron’s AP Statistics volume focuses primarily on the connection between math and statistics. 

Of course, mathematical algorithms and calculations are at the core of this field as well as data science. However, other books only focus on one aspect, excluding some of the basics of math. 

This affordable book is also easy to read and highly accessible. Inside, you will find 15 chapters – one for each basic concept of statistics. While some might not be covered particularly in-depth, you can get an all-around knowledge of a subject.

If you would like to practice, this book includes a CD to watch and tests that you should be able to pass at the end of every chapter. Answers to the questions are also included to enable self-learning.

• Accessibility: available online at the cost of around $9. On eBay, you can find cheaper second-hand versions.
• Experience level: beginners and experts looking at specializing 
• Best for: beginner statisticians interested in the link between math and statistics

Statistics for Business and Economics – James T. McClave, P. George Benson and Terry T. Sincich

This book is the brainchild of a series of experts in the fields of math, finances, market trends, and statistics. Unlike the option seen above, this book primarily focuses on the applications that statistics find in the world of business and economics. 

The fact that the authors have brought their own experience into the making of this book offers students the opportunity to work with real-world examples and truthful reports. You can find traces of these stories in the example used, as well as in tests and exercises. 

Another aspect of Statistics for Business and Economics worth mentioning is the fact that this book is organized in easy-to-read chapters that revolve around a relevant case study. These real-world instances are used to explain a new concept of statistics to the students.

One of the main advantages of this type of learning technique is that you are likely to find the content more motivating and engaging. This is not always true in the case of statistics books that don’t refer so much to real-life scenarios and practical applications.

• Accessibility: available in a range of formats, with prices varying from $10 to $150
• Experience level: beginner and intermediate
• Best for: statistic students interested in business application and real-world data

Naked Statistics: Stripping the Dread From the Data – Charles Wheelan

If you have been waiting to find a book that would make you fall in love with statistics, at first sight, you have found it. This book is a little irreverent, and it has a unique point of view over the always-considered serious and monotone field.

Funny and accessible, this book is created to be an optimal choice for everybody, whether you are a navigated student, amateur statistician, or just curious about a field that can open so many career opportunities.

While using real-world examples and easy-to-read chapters, this relatively small volume works perfectly for everybody who is looking for an alternative introduction to statistics. 

Of course, you might need to complement this book with another, more in-depth volume that can explain in more detail some main topics. However, if you were not sure whether statistics is the field for you or not, Naked Statistics can give you an immediate answer!

• Accessibility: it is available online, with a cost ranging between $7 and $9. You can also opt for the free Audible version.
• Experience level: beginners, curious
• Best for: students interested in the real-world application of statistics with a fun twist.

Practical Statistics for Data Scientists – Peter Bruce

The complete title of this book is Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python. This headline says a lot about how useful this modern volume could be when starting out your career in data science.

While focusing on the notions of data science and the use of R, this book brings the attention of the readers on the fact that not many data scientists have formal training in statistics. Nonetheless, this whole discipline is founded in the field of statistics.

Instead, this book starts with the statistical concepts and tells you what the best use you could make of them in the field of data science. The chapters cover:

• Importance of exploratory data in data science
• Random sampling
• Experimental design’s principles
• Regression
• Detection of anomalies
• Prediction
• Statistical machine learning methods 
• Unsupervised learning methods

These are just among the concepts you will learn in this book, but several of the chapters explore in-depth other techniques that can be used in Data Science.

• Accessibility: around $40 if bought online. There is also a free version available in PDF format if you don’t feel like committing to a significant expense.
• Experience level: beginner-intermediate. Knowledge of R preferred
• Best for: Statisticians who are looking at using Python and R
• Free PDF: Practical Statistics for Data Scientists 

Head First Statistics: A Brain-Friendly Guide – Dawn Griffiths

One of the selling points of this accessible volume is the fact that it tries to make fun and to entertain a subject such as statistics – and it succeeds in it. Firstly, you will be able to find simplified concepts and explanations of jargon and acronyms. 

Alone, these two characteristics would be enough for you to move onto your studies further. However, this book does not stop here. Indeed, reading the different chapters, you will explore all the major concepts of statistics, including the ones that are the most suitable for data science projects.

The puzzles, visual aids, case studies, and real-world examples included in this book make sure it fits in the top more interesting books to learn statistics for data science. 

• Accessibility: online cost varying between $7 and $23
• Experience level: beginners
• Best for: students interested in concepts but not in terms and jargon

Introduction to Statistical Learning – Gareth James

If you are looking for a complete, all-encompassing introduction to the field of Statistical Learning, this volume is the right one for you. However, the book focuses on the explanations of how to use large data sets to allow a pattern to emerge. 

Therefore, if you want to launch a career in data science, this book should already be in your shopping cart.

Inside, you will be able to find real-world examples, graphs, charts, and case studies that can help simplify even the most complex concept. R – the preferred programming language by data scientists – is used for the analysis of certain situations, so you have a complete toolkit to start practicing in the field.

• Accessibility: the cost varies depending on the format and can be as high as $50. The volume is also available on Springer.
• Experience level: beginner, but linear regression knowledge is assumed
• Best for: students with a basic level of mathematical knowledge

Think Stats – Allen Downey

Think Stats is a modern, easy-to-read book that can help you refine your skill as a statistician and data scientist. This book focuses on the use of programming languages such as R and Python to perform tasks such as statistical analysis instead of completing the process mathematically.

To have an all-encompassing knowledge of the process. This book uses a single case study throughout the book. This case study will show you how to gather the data, analyze them, and draw conclusions from them.

Since you will be using real-world data during your training, you will also acquire some statistical knowledge that is useful in data science.

• Accessibility: between $20 and $40
• Experience level: beginner statisticians with experience in computing sciences or programming. Knowledge of coding and programming is assumed.
• Best for: students who want to upgrade their skills and use statistics within their current project.

All of Statistics: A Concise Course in Statistical Inference – Larry A. Wasserman

It is not exactly as the title of the book says – it does not cover all of the statistics. It is fair to say that this statistical book helps you discover a much greater range of concepts than most other introductory books, but it might not show you an in-depth look of all the characteristics of certain models and notions.

If you are already familiar with statistical aspects, reading this book can broaden your career-related horizon. Moreover, unlike other more traditional books about stats, this volume includes the latest innovations and the most modern upgrades on staple concepts of statistics.

• Accessibility: parts available on SpringerLink. The whole volume is accessible for minimal cost.
• Experience level: introductory book on mathematical statistics
• Best for: beginners 

Statistics – David A. Freedman

While not among the most recent books on statistics, this volume contains basic notions and staple concepts that are useful in many fields. 

Whether you wish to take your education further and specialize in data science or you wish to pursue a project’s research, this book will give you all the fundamentals you need to face most tasks.

If you are worried about the lack of new concepts and innovations, keep in mind that new editions are released regularly for the benefits of students and professionals alike.

• Accessibility: free PDF version available. Otherwise, it can cost between $50 and $100.
• Experience level: beginners
• Best for: beginners who are looking to cover all the main concepts of statistics

Innumeracy: Mathematical Illiteracy and Its Consequences – John Allen Paulos

First published in 1988, this bestseller asks why it is important to understand mathematical and statistical sciences. 

In the pages of Innumeracy, you will be able to find out about the consequences of innumeracy and the benefits of having control over it. Mathematics and statistics are indeed used in many aspects of societies, including lotteries and insurance firms. 

Understanding how probability and trends are functioning can offer you better control over what is happening in your life.

If you know that you have always been interested in the field of statistics, but you are not sure what you will do with the knowledge acquired, go ahead and purchase this book. 

• Accessibility: available online for $4 to $7
• Experience level: beginner/curious
• Best for: someone who wants to know more about the importance of learning more about math and stats – and, of course, data science.

The Elements of Statistical Learning: Data Mining, Inference, and Prediction – Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie

It is essential to understand what is the concept of statistics that you are bound to use in data science. Indeed, statistics is an extremely broad field that might include concepts not useful in other disciplines.

However, if you are looking for a book that can help you refine the skills needed for data science, the knowledge presented in this book is what you need. Indeed, many companies rely on processes such as data mining, prediction, and inference to create analytical models that can be used in real life.

Unfortunately, there is a limited number of books on the market that will be as clear as this one when explaining such complex processes. Luckily, though, a free PDF version is available for you to grab.

• Accessibility: the free PDF gives you accessibility to this resource every time you need it.
• Experience level: intermediate
• Best for: learners looking at deepening their knowledge in data mining and prediction models
• Free version: The Elements of Statistical Learning 

Discovering Statistics Using R – Andy Field, Jeremy Miles, and Zoë Field

While you won’t need to have an exhaustive knowledge of statistics to enjoy this book, it is recommendable to get to know better the functions of R. this statistical language often used by data scientists is based on a statistical language that enables programmers to leverage the speed and efficiency of a programming language and the ingenious statistical models.

Unlike many other structured books on the market today, this volume is written in a witty, irreverent tone that can help you get involved in the field more. You can also find self-assessment tests and quizzes to test your knowledge as you continue reading. 

Don’t underestimate the importance of a book written in an engaging tone, especially if the book in question is about statistics. 

• Accessibility: from $18 to $190 (for hardback cover)
• Experience level: intermediate – experience in programming and knowledge of basic concepts of stats is assumed
• Best for: using R in your career

A Probabilistic Theory of Pattern Recognition – Luc Devroye

The last book on our list is the self-contained volume written by Luc Devroye. The chapters of this book cover a huge range of techniques and statistical processes that you will be able to use when working in data science. 

Among the most important ones, you will find nearest neighbor rules, parametric classification, and feature extraction. Just like the previous book, you will be able to find tests and quizzes at the end of every section.

• Accessibility: from $70 to $180
• Experience Level: intermediate
• Best For statisticians and data scientists looking at refining their knowledge

Considerations and Features of the Best Statistics Books for Data Science

As mentioned, statistics are among the most difficult subjects to learn just by reading a book. When it comes down to applying the notion learned in such a practical and evolving field like data science, it is essential to couple up your theoretical knowledge with practical skills. 

However, if you would like to start your journey in this industry from a book, there are some critical characteristics to keep in mind. Even if you have opted for a book different from the ones mentioned above, make sure it boasts the following characteristics – you can do so by checking out the reviews on these books on platforms such as Amazon.

Easy to Understand

Firstly, a book about statistics should be easy to understand. Statistics and data science, just like other fields, use abbreviations and jargon that can make learning more about the field much more challenging. 

However, there are books that avoid such terms at first, just to explain the meaning of certain phrases, abbreviations, or common terms later on. 

Such a learning method can help you arrive at the phase in which you need to apply the notions learned fully prepared. And, when you are applying for a data science job, you will sound like a pro.

Telltale signs of the intelligibility of the book can be found in the volume’s reviews or in the introduction.

Practical Applications Opportunities

Some books are purely theoretical, which are excellent if you are looking at learning statistics for research. However, this field found its foundation on user-generated and real-world data. And these are everything aside from theoretical values.

When you need to apply such notions to data science, the need for practical uses becomes paramount. Indeed, data science is an interdisciplinary field in which data gathered by companies is used to study past trends and foresee future developments.

Making sure that your book encourages you to try the notions learned in real-life scenarios is crucial if you are looking to work for a company or business in the field of data science.

Include Calculation Tips

There is no doubt about the fact that statistics is a field based on calculations, algorithms, and math in general. But some tips can help.

As an example, you could find a book that offers a satisfactory introduction about some statistical or predictive models, without actually teaching you how to extract measurable results. 

While these books might be easy to understand at first, they might leave you without the substantial knowledge needed to put such notions into practice. 

To check whether a textbook has everything you need, look for exercises and problems to solve at the end of each chapter. And of course, it should include some tips on how to use your calculator properly. 

It Is Easily Accessible

Depending on your budget and commitment to learning more about data science, you might be willing to spend more or less on volumes, books, and resources.

However, luckily, some resources are available to all students at all times. So, instead of spending money on buying just one volume and taking a chance on it, you can have a collection of various works that you can use as a reference while entering this field as a professional.

Avoid renting or borrowing these books as having a physical reference to go back to when you have a seemingly insurmountable problem can be time- and energy-saving.

Can Be Used in Combination With Other Learning Methods

Some of the books seen above come with DVDs or CDs that can help you get some of the insights explained in the book in other forms. These methods are particularly useful for visual or auditory learners who need a reference other than a textbook. 

If the volume you have picked does not come with another learning channel, there is no need to discard it altogether. However, in this case, you might consider subscribing to platforms such as Udemy and SkillShare to deepen your knowledge and apply the notions learned.

Conclusion

The books mentioned above are the ones you can use to start learning statistics for data science. Every learner might prefer different methods to acquire and retain information about this ever-changing field. 

While these amazing books are well-crafted for you to get a head start in the field, don’t forget to increase your practical knowledge by subscribing to online courses or specialized training. For example, you might like to start applying the notions learned in R or increase your knowledge of useful programming languages like Python. 

Ultimately, a lot depends on the career you would like to build for yourself in this field.

BEFORE YOU GO: Don’t forget to check out my latest article – 6 Proven Steps To Becoming a Data Scientist [Complete Guide]. We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and created this comprehensive guide to help you land that perfect data science job.

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