Search for books, people and lists
Read This Twice
HomePeopleBooksSonaLibrariesSign In

Best Statistics Books

Recommendations from 29 articles, Bill Gates, Neil deGrasse Tyson, Ev Williams and 49 others.
Best Statistics Books
98 books on the list
Sort by
Number of Articles
Naked Statistics book cover
Naked Statistics
Stripping the Dread from the Data
Charles Wheelan - 2014-01-13 (first published in 2012)
Goodreads Rating
Discover the exciting world of statistics and its real-world applications in Naked Statistics. In this engaging book, Charles Wheelan simplifies complex concepts and shows us how data and statistics can be used to answer pressing questions, from cheating schools to rising autism rates. With insightful examples, including Schlitz Beer marketers and Let's Make a Deal, Wheelan brings statistics to life and strips away the technical details to focus on intuition. For those who struggled through Stats 101 or anyone curious about the power of data, Naked Statistics is a must-read.
Practical Statistics for Data Scientists book cover
Practical Statistics for Data Scientists
50+ Essential Concepts Using R and Python
Peter Bruce - 2020-06-02
Goodreads Rating
This book is a must-have for aspiring data scientists who lack formal statistical training. It explores statistical methods from a data science perspective and provides practical guidance on their application. The second edition includes comprehensive examples in Python and advice on avoiding their misuse. You'll learn all about exploratory data analysis, random sampling, experimental design, regression, and more. Plus, the book covers unsupervised learning methods for extracting meaning from unlabeled data. If you're familiar with R or Python and have some exposure to statistics, this accessible reference will bridge the gap for you.
An Introduction to Statistical Learning book cover
An Introduction to Statistical Learning
with Applications in R (Springer Texts in Statistics)
Gareth James - 2017-09-01 (first published in 2013)
Goodreads Rating
Learn how to make sense of complex data sets with An Introduction to Statistical Learning. This must-read book covers essential statistical learning techniques, including linear regression, classification, resampling methods, and more. With real-world examples and step-by-step tutorials on implementing the analyses in R, this accessible book is perfect for practitioners in science, industry, and other fields. Whether you're a statistician or non-statistician, this book will help you use cutting-edge techniques to analyze your data.
Statistics in Plain English book cover
Statistics in Plain English
Timothy C. Urdan - 2005-02-22 (first published in 2001)
Goodreads Rating
A straightforward and accessible guide to statistics, this textbook covers the basics and beyond, from central tendency to advanced concepts like regression and ANOVA. Each chapter includes a short description of the statistic, an in-depth explanation, an example, and a glossary of terms. The fourth edition features work problems and examples from the author's own data and published research, as well as a website with PowerPoint presentations, interactive problems, and more. Perfect for undergrad or graduate statistics courses, or as a reference tool for anyone interested in refreshing their memory.
Think Stats book cover
Think Stats
Exploratory Data Analysis
Allen B. Downey - 2011-07-22
Goodreads Rating
Learn how to turn data into knowledge with an introduction to statistical analysis using Python. By working through a single case study, this book teaches the entire process of data analysis, from collecting data to identifying patterns and testing hypotheses. Discover distributions, rules of probability, visualization, and more through writing and testing code. With new chapters on regression, time series analysis, survival analysis, and analytic methods, gain a deeper understanding of statistical inference to answer real-world questions.
The Elements of Statistical Learning book cover
The Elements of Statistical Learning
Data Mining, Inference, and Prediction (Springer Series in Statistics)
Trevor Hastie - 2003-07-30 (first published in 2001)
Goodreads Rating
Discover the world of data mining and machine learning with this comprehensive guide. Written by three prominent professors of statistics, this book provides a common conceptual framework for understanding the tools and ideas in various fields such as medicine, biology, finance, and marketing. With a focus on concepts rather than mathematics, it covers a broad range of topics including neural networks, support vector machines, classification trees, and boosting. With many examples and color graphics, this is a valuable resource for statisticians and anyone interested in data mining in science or industry.
Statistics Done Wrong book cover
Statistics Done Wrong
The Woefully Complete Guide
Alex Reinhart - 2015-03-16 (first published in 2013)
Goodreads Rating
Learn how to avoid common statistical fallacies and analyze data correctly with "Statistics Done Wrong". This book offers cautionary tales of mistakes made by even the most knowledgeable scientists and teaches you the best practices for avoiding those errors. Discover the ideas behind hypothesis testing and regression analysis, how to ask the right questions, design experiments, and work with data. Through colorful examples of statistics gone awry, this book offers approachable lessons for proper methodology, and pro tips for practicing scientists and statisticians. Improve your data analysis skills with "Statistics Done Wrong".
All of Statistics book cover
All of Statistics
A Concise Course in Statistical Inference (Springer Texts in Statistics)
Larry Wasserman - 2003-12-04
Goodreads Rating
Learn probability and statistics quickly with this book, covering a broad range of topics beyond typical introductory math books. Perfect for graduate or advanced undergrads in computer science, math, statistics, and related disciplines. Get familiar with modern topics like nonparametric curve estimation, bootstrapping, and classification, without needing prior knowledge. Discover the intersection of statistics, data mining, and machine learning, and how statisticians and computer scientists are working together to advance these fields.
AP Statistics with Online Tests book cover
AP Statistics with Online Tests
Martin Sternstein - 2019-07-02
Goodreads Rating
Prepare for the AP Statistics exam with Barron's comprehensive review, practice tests, and expert explanations. This edition includes 5 full-length practice tests in the book, 3 online practice tests, and a diagnostic test to help identify strengths and weaknesses. Also included is subject review for all test topics, additional practice questions with answers, end-of-chapter quizzes with detailed answer explanations, and a guide on using graphing calculators.
Head First Statistics book cover
Head First Statistics
A Brain-Friendly Guide
Dawn Griffiths - 2008-09-02
Goodreads Rating
Discover the fascinating world of statistics with an engaging and interactive book that brings this typically dry subject to life. With Head First Statistics, you'll learn everything you want and need to know about statistics through thought-provoking material, full of puzzles, stories, quizzes, and real-world examples. Whether you're a student or just curious, this brain-friendly formula helps you get a firm grasp of statistics so you can understand key points and actually use them. Master topics such as probability, expectation, sampling, regression, hypothesis testing, and much more. Ideal for high school and college students, Head First Statistics satisfies the requirements for passing the AP Statistics Exam. Get ready to see how statistics work in the real world!
Bayesian Data Analysis by Andrew Gelman
The Signal and the Noise by Nate Silver
How Not to Be Wrong by Jordan Ellenberg
The Art of Statistics by David Spiegelhalter
Pattern Recognition and Machine Learning by Christopher M. Bishop
Computer Age Statistical Inference by Bradley Efron
OpenIntro Statistics by David M Diez
Bayesian Methods for Hackers by Cameron Davidson-Pilon Davidson-Pilon
Statistics by AI Publishing
Statistics II for Dummies by Deborah J. Rumsey
How to Lie with Statistics by Darrell Huff
Innumeracy by John Allen Paulos
You Are Not So Smart by David McRaney
Statistics, 11th Edition by Robert S. Witte
The Complete Idiot's Guide to Statistics by Robert A. Donnelly Jr.
Statistics for Business and Economics by James T. McClave
The Visual Display of Quantitative Information by Edward R. Tufte
How to Talk So Kids Will Listen & Listen So Kids Will Talk by Adele Faber
Introduction to Algorithms by Thomas H. Cormen
Thinking, Fast and Slow by Daniel Kahneman
Business Analytics Study Guide by Habiba Emadi Keshtiar
ANALYTICS by Henry Gersh
Applied Predictive Modeling by Max Kuhn
Judgment Under Uncertainty by Daniel Kahneman
R for Data Science by Hadley Wickham
Understanding Probability by Henk Tijms
Probability Theory by E. T. Jaynes
Ready, Study, Go! by Khurshed Batliwala, Dinesh Ghodke
Python Data Science Handbook by Jake Vanderplas
Mastering 'Metrics by Joshua D. Angrist
Ace the Data Science Interview by Nick Singh, Kevin Huo
Mostly Harmless Econometrics by Joshua D. Angrist
Statistics for Economics - Class 11 - CBSE (2020-21) by TR Jain and VK Ohri
Statistics in Psychology and Education by S.K. Mangal
Statistics Economics for Class 11 (Examination 2020-2021) by
Nursing Research and Statistics by Sharma
Bill James Baseball Abstract, 1986 by Bill James
Data Analysis Using Regression and Multilevel/Hierarchical Models by Andrew Gelman
Statistical Methods (Combined Vol), 1Ed by DAS
Confident Data Skills by Kirill Eremenko
Introduction to Probability by Dimitri P. Bertsekas
Introductory Econometrics by Jeffrey M. Wooldridge
A Student’s Guide to Bayesian Statistics by Ben Lambert
An Introduction to Probability Theory and Its Applications by William Feller
Statistical Inference by Casella, George, Berger, Roger L. [Cengage Learning, 2001]2nd edition [Hardcover] by Roger L. Berger George Casella
Numerical Recipes 3rd Edition by William H. Press
Fifty Challenging Problems in Probability with Solutions by Frederick Mosteller
Statistics for Experimenters by George E. P. Box
Cracking the AP Statistics Exam, 2020 Edition by The Princeton Review
Probability Theory by Y. A. Rozanov
An Adventure in Statistics by Andy Field
Data Analysis by Devinderjit Sivia
Statistics For Economics & Introductory Microeconomics For CBSE Class 11 - 2021-2022 Session by
Statistics Without Tears by Aa
A Hands-On Introduction to Data Science by Chirag Shah
Statistics for Economics - Class 11 - CBSE (2021-22) by TR Jain
Pattern Classification 2nd Edition with Computer Manual 2nd Edition Set by Richard O. Duda
A Course in Probability Theory, Third Edition by Kai Lai Chung
Statistical Methods in the Atmospheric Sciences by Daniel S. Wilks
The Probability Tutoring Book by Carol Ash
Info We Trust by RJ Andrews
Data Science and Big Data Analytics by Emc Education Services
Statistical Methods in Bioinformatics by Warren J. Ewens
Empirical Methods for Artificial Intelligence by Paul R. Cohen
Statistics by R S N Pillai
Machine Learning Cookbook with Python by Rehan Guha
Honest Rainmaker by A. J. Liebling
Student Study Guide to Accompany Statistics Alive! 2e by Wendy J. Steinberg by Wendy J. Steinberg
Data Analysis In Business Research by D Israel
Statistics for Machine Learning by Himanshu Singh
Probability Theory and Statistical Applications by Peter Zörnig
Basic Probability by Henk Tijms
Statistics Made Easy by Alan Graham
Statistics for Economics by Dr D P Jain
Probability for Statistics and Machine Learning by Anirban DasGupta
Data Science from Scratch by Joel Grus
Principles of Statistics by M. G. Bulmer
Statistics by David Freedman
First Course in Probability, A by Sheldon Ross
The Lady Tasting Tea by David Salsburg
The Model Thinker by Scott E. Page
Statistics by E. Wayne Courtney
Statistics Crash Course for Beginners by AI Publishing
How Animals Work by Schmidt-Nielsen
Modern Mathematical Statistics with Applications by Jay L. Devore