# Free statistical textbooks

Are there any free statistical textbooks available?

• Look at Statistics Topics ebook on Amazon by Mehta, and his free web log Statistics Ideas that has lecture slides. Nearly free and better in some pedagogical topics, than the ones you cite on your list of resources. – user48690 Jun 20 '14 at 0:16

The most widely used and probably the best of what is available is http://www.statsoft.com/textbook/

Other online stats books include

Update: I can now add my own forecasting textbook

The Elements of Statistical Learning by Hastie, Tibshirani, and Friedman is a standard text for statistics and data mining, and is now free:

https://web.stanford.edu/~hastie/ElemStatLearn/

Also Available here.

• Why pay $70 for the book? To support the authors and to have a physical copy. That's why I did it, anyway! – Shane Jul 23 '10 at 17:13 • I agree with Shane... and a hardcopy makes reading it much easier. – Vince Jul 24 '10 at 0:07 • Did that, too (previous edition). But it is nice to be able to look things up online when the book is not at hand. And to have access to the new edition. – cbeleites Aug 17 '12 at 12:03 • (+1) Just wanted to comment that this is a GREAT book, it is my all-time favorite. I also ordered a physical copy of it :-). – Néstor Aug 20 '12 at 3:13 • If you attend Hastie and Tibshirani's Statistical Learning and Data Mining seminar, you'll receive a free copy of the text. And you can have your book signed! – RobertF Feb 26 '13 at 18:36 We're looking for long answers that provide some explanation and context. Don't just give a one-line answer; explain why your answer is right, ideally with citations. Answers that don't include explanations may be removed. • Michael Lavine is a clear lecturer and thinker, so I have little doubt his book is worth a look. – whuber Oct 8 '10 at 20:26 • I'm teaching out that book this semester. It may be a good statistics book, but I'm having second thoughts regarding its light probability content. – John D. Cook Oct 9 '10 at 1:21 There's a superb Probability book here: http://www.dartmouth.edu/~chance/teaching_aids/books_articles/probability_book/book.html which you can also buy in hardcopy.; I've often found the Engineering Statistics Handbook useful. It can be found here. Although I've never read it myself, I hear Introduction to Probability and Statistics Using R is very good. It's a full ~400 page ebook (also available as an actual book). As a bonus, it also teaches you R, which of course you want to learn anyways. • +1 For this resource. As the name says, excellent for a practical approach to engineering problems. – Bossykena Jul 26 '10 at 17:42 • first link is dead. – Bru Jul 12 '17 at 8:16 I really like The Little Handbook of Statistical Practice by Gerard E. Dallal Here's a fresh one: Introduction to Probability and Statistics Using R . It's R-specific, though, but it's a great one. I haven't read it yet, but it seems fine so far... ## Machine Learning$\hskip{5em}$Switching now to more specialized topics, there are:$\hskip{4em}$OpenIntro Statistics http://www.openintro.org/stat/textbook.php Inexpensive paperback copies are also available on Amazon. • I moved this from answer to comment since I am expressing my opinion about free books on the net rather than providing a a list of some. As both an author and owner of books I see both sides. I appreciate that most statistics books, especially when they deal with specialized topics are very expensive. However as an author who has put in a lot of effort to try to write useful and informative books I think the authors and publishers deserve remuneration for the efforts they go through to produce the books. So I don't think books should be free. – Michael Chernick Aug 17 '12 at 21:13 • But if authors want to put out material on the internet for free that is their choice. We all can benefit from that. – Michael Chernick Aug 17 '12 at 21:14 • You could make the same arguments about software, but we all benefit from R. – Jeremy Miles Mar 2 '15 at 3:47 A New View of Statistics by Will G. Hopkins is great! It is designed to help you understand how to understand the results of statistical analyses, not how to prove statistical theorems. We're looking for long answers that provide some explanation and context. Don't just give a one-line answer; explain why your answer is right, ideally with citations. Answers that don't include explanations may be removed. Norman Matloff has written a mathematical statistics textbook for computer science students that's free. Kind of a niche market, I suppose. For what it's worth, I haven't read it, but Matloff has a Ph.D. in mathematical statistics, works for a computer science department, and wrote a really good R book, that I recommend for people who want to go to the next stage of programming R better (as opposed to just fitting models with canned functions). Not Statistics specific, but a good resource is: http://www.reddit.com/r/mathbooks Also, George Cain at Georgia Tech maintains a list of freely available maths texts that includes some statistical texts. http://people.math.gatech.edu/~cain/textbooks/onlinebooks.html I really like these two books by Daniel McFadden of Berkeley: http://elsa.berkeley.edu/users/mcfadden/e240a_sp98/e240a.html http://elsa.berkeley.edu/users/mcfadden/e240b_f01/e240b.html We're looking for long answers that provide some explanation and context. Don't just give a one-line answer; explain why your answer is right, ideally with citations. Answers that don't include explanations may be removed. For getting into stochastic processes and SDEs, Tom Kurtz's lecture notes are hard to beat. It starts with a decent review of probability and some convergence results, and then dives right into continuous time stochastic processes in fairly clear, comprehensible language. In general it's one of the best books on the topic -- free or otherwise -- I've found. "An Introduction to Statistical Learning with Applications in R" http://www-bcf.usc.edu/~gareth/ISL/ by two of the 3 authors of the well-known "The Elements of Statistical Learning" plus 2 other authors. An Introduction to Statistical Learning with Applications in R is written at a more introductory level with less mathematical background required than The Elements of Statistical Learning, makes use of R (unlike The Elements of Statistical Learning), and was first published in 2013, some years after this thread was started. Some free Stats textbooks are also available here. We're looking for long answers that provide some explanation and context. Don't just give a one-line answer; explain why your answer is right, ideally with citations. Answers that don't include explanations may be removed. Statsoft's Electronic Statistics Handbook ('The only Internet Resource about Statistics Recommended by Encyclopedia Britannica') is worth checking out. Cosma Shalizi, CMUs ML guru, occasionally updates a draft of a stats book soon to be published by Cambridge Press titled Advanced Data Analysis from an Elementary Point of View. Can't recommend it highly enough... Here's the Table of contents: I. Regression and Its Generalizations Regression Basics The Truth about Linear Regression Model Evaluation Smoothing in Regression Simulation The Bootstrap Weighting and Variance Splines Additive Models Testing Regression Specifications Logistic Regression Generalized Linear Models and Generalized Additive Models Classification and Regression Trees II. Distributions and Latent Structure Density Estimation Relative Distributions and Smooth Tests of Goodness-of-Fit Principal Components Analysis Factor Models Nonlinear Dimensionality Reduction Mixture Models Graphical Models III. Dependent Data Time Series Spatial and Network Data Simulation-Based Inference IV. Causal Inference Graphical Causal Models Identifying Causal Effects Causal Inference from Experiments Estimating Causal Effects Discovering Causal Structure Appendices Data-Analysis Problem Sets Reminders from Linear Algebra Big O and Little o Notation Taylor Expansions Multivariate Distributions Algebra with Expectations and Variances Propagation of Error, and Standard Errors for Derived Quantities Optimization chi-squared and the Likelihood Ratio Test Proof of the Gauss-Markov Theorem Rudimentary Graph Theory Information Theory Hypothesis Testing Writing R Functions Random Variable Generation  • I point people to Cosma's notes regularly. There's some good material in there – Glen_b Jun 6 '16 at 1:10 I know other authors have gone to some trouble to make their books available here on stack exchange ... The printed version of our 2002 edition was printed 3 times and sold out 3 times; Springer and Google recently started selling it (book only) as a PDF eBook (no software) on the Springer and Google sites for$79.

We are delighted to be able to make the PDF eBook version (2002 edition) available for FREE to stackexchange users at:

http://www.mathstatica.com/book/bookcontents.html

This is a complete PDF version of the original 2002 printed edition. Although no software is included (neither Mathematica nor mathStatica), the methods, theorems, summary tables, examples, exercises, theorems etc are all useful and relevant ... even as a reference text for people who do not even have Mathematica.

• chapter by chapter.

iBooks installation

To install as an iBook:

• Then drag it into iBooks (under the section: PDF files).

• First install it as an iBook (as above)

A write up of probability tutorials and related puzzles along with R code for learning. Hope it helps

We're looking for long answers that provide some explanation and context. Don't just give a one-line answer; explain why your answer is right, ideally with citations. Answers that don't include explanations may be removed.

Not properly an entire textbook, but the part IV of Mathematics for Computer Science is about probability and random variables.

http://www.probabilitycourse.com/ is a website hosting free online-based Probability and Statistics textbook. It also has extra features such as graphing tools and lecture videos

Here is also a great free book on multivariate statistics by Marden, primarily concerned with the normal linear model linked on this page:

http://istics.net/stat/pages/Statistical%20education/Statistics%20text%20books-%20Free%20and%20not%20free.html

It's not a textbook but Bayesian Methods in the Search for the MH370 is a great introduction to particle filters.

A digital textbook on probability and statistics by M. Taboga can be found at https://www.statlect.com The level is intermediate. It has hundreds of solved exercises and examples, as well as step-by-step proofs of all the results presented.

## protected by whuber♦Mar 1 '15 at 22:35

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