If you don't know where to start your educational journey with stats, our top 3 picks of the best statistics books for Data Science in this blog post will help you make your first steps.
There are lots of statistics books for Data Science, but where should you start and which ones should you read first?
This post will help you make those decisions and hopefully guide you to a longer, stronger career in Data Science.
To start out with, I'll make recommendations on the best statistics books for Data Science.
From here I'll show you the top books in some of the easier topics in statistics; from the best probability books for beginners to the best regression books.
Then I'll give you my pick of the best books on statistics for Data Science in some slightly harder subjects; the best multivariate statistics books, the best Bayesian statistics books and the best time series analysis books.
By the time you've got a working knowledge of each of these areas your Data Science skills will really be in great demand!
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Why Do We Need Statistics?
Statistics is more than just a set of statistical tests.
It is a roadmap that helps you to use proper methods to collect and organise data, use appropriate methods of analysis to yield correct interpretation and effectively present the results in a way that inspires your audience.
It is how we make discoveries in science, make decisions based on data and make predictions of what the future will look like.
Our picks of the best books on statistics for Data Science will help you build that roadmap in your own research so you'll have the confidence to know that the discoveries you make are based on good science.
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Do I Need to Know Statistics For Data Science?
In short, yes.
A few years ago, in the rush for programmers to convert themselves into Data Scientists (mainly to earn more money for doing the same job), they learnt how to use a few new tools for handling and plotting data, and for machine learning.
Most of these were plug-and-play, so as long as you could use the tool, you could get believable results out of the other end.
"Statistics? We don't need no stinkin' statistics! Didn't you get the memo? Data science is the sexiest job of the 21st century!"
And then people who had some experience working with data started to ask awkward questions about the results. And they didn't stack up.
And that's because statistics is the scaffold on which good Data Science is built. If you're not using statistics in your Data Science, you're building a house of cards.
Data Science may still be the sexist job of the 21st century, but the sexiest subject of Data Science is statistics!
OK, so it's not the sexiest, but it is the most important...
The books in this post are some of the very best statistics books for Data Science, so you can be sure that they'll help you build your scaffold properly!
3 Must-Read Books on Statistics for Data Science @chi2innovations #statistics #datascience
Can You Learn Statistics On Your Own?
This is the easiest question about statistics to answer - yes, yes, yes - absolutely yes!
Statistics may have a reputation as being difficult to learn, but it's an undeserved reputation - most people that have to do statistics in their research have never had any statistical training, and never will.
If they can do it, so can you!
For most people, learning to do the basics well is all they'll ever need, and they can leave the hard stuff to the guys with PhDs in stats.
For the rest of us (including me), statistics is about learning to make consistently good decisions about data, and the basics will get you there.
The statistics books for Data Science in this post will certainly help you on that journey!
Top 3: Best Statistics Books For Data Science
In this post - the 3rd in a series of 8 in which we bring you 21 Inspirational Books for All Aspiring Data Scientists, we highlight 3 of the best statistics books for Data Science:
They are all for beginners, are very entertaining and give you a great idea of how to do stats right - and how to spot when they're wrong!
If our pick of the best statistics books for Data Science doesn't inspire you, there are some more recommendations further down the post for some more in-depth subjects.
If you're looking for the best probability books for beginners or the top regression books, you'll find them there.
You'll also find our recommendations for the best multivariate statistics books, the best Bayesian statistics books and the best time series analysis books too.
Something for everyone!
Stripping the Dread from the Data
Clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal – and you’ll come away with insights each time.
Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called “sexy”. From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.
For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.
And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal – and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.
Practical Statistics for Data Scientists
50+ Essential Concepts Using R and Python
Peter Bruce and Andrew Bruce
The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not...
Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not.
Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.
With this book, you’ll learn:
Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You’d be surprised how many scientists are doing it wrong.
Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You’ll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics.
You’ll find advice on:
Another 3 of the Best Statistics Books For Data Science
There are just sooooo many great statistics books for Data Science that I found it difficult to whittle it down to just 3, so here are another 3 of the best statistics books for Data Science:
Best Probability Books For Beginners
If our list of the best statistics books for Data Science isn't quite what you're looking for, perhaps you're looking for something more specific.
If so, maybe a list of the 3 best probability books for beginners might just hit the spot:
Best Regression Books
Or maybe you need to brush up on your regression. If so, we've got just the regression books for you.
Here's a list of our favourite regression books for your bookshelf:
Best Multivariate Statistics Books
For those of you that aren't beginners and are looking to go to the next stage, maybe it's time to look into multivariate statistics.
This is a really tricky subject, and you'll need the best multivariate statistics books to help you along. Here are a good selection from the many on offer:
Best Bayesian Statistics Books
Talking about harder subjects, maybe Bayesian statistics is an area you'd like to transition to. If so, here is our pick of the best Bayesian statistics books to help you out:
Best Time Series Analysis Books
And while we're on the subject of harder subjects we might as well drop into time series analysis. Here are a few time series analysis books you might like to check out:
If books aren't really your thing and you prefer to learn by video course, we have a post dedicated to The Best Statistics Courses Online.
Check them out - you won't be disappointed!
Best Statistics Books For Data Science - Summary
I hope you enjoyed our pick of the best statistics books for Data Science. Between them, these statistics books will give you an excellent start in making sure your Data Science career is built on a solid platform.
If you have the time, I suggest you pick one from each on the list of the easier subjects; the best probability books for beginners and the regression books.
Once you've done that, pick one from each of the harder subjects; the best multivariate books, the best Bayesian statistics books and the best time series analysis books.
Once you have a working knowledge of each of these areas your skills will be very much in demand!
If you've read any of these books, please leave a comment below.
Did you enjoy them? Did you learn something new? Did any of them take your data science skills to a new level?
If you think there are any other, better, books that should be on this list of the best statistics books for Data Science - let me know. I might just change my recommendations...