The 10 Best Statistics Textbooks

OpenIntro Statistics covers a full first college course, from describing data through probability, hypothesis tests and both straight-line and logistic regression, and its three authors give the PDF away. A bound copy mainly saves your printer and your eyes. Each section has short videos and slides, and the labs come in R, Python and several other programs. Teachers can get full solutions. The print copy is black and white, so color-coded graphs lose some meaning.

If math makes you nervous, start with Statistics for People Who (Think They) Hate Statistics. Neil Salkind and Bruce Frey explain each idea in a chatty, joking voice, then walk through one test at a time: averages, correlation, t-tests, analysis of variance and chi-square. Chapters end with practice questions and answers. It fits social science, education and health courses well. It skips most probability theory, so math and economics majors will want more depth.

The Art of Statistics teaches how to think with data rather than how to crunch it. David Spiegelhalter, a Cambridge statistician and a past president of the Royal Statistical Society, builds each chapter around a real question, such as who survived the Titanic or how a murderous doctor might have been caught sooner. Sampling, uncertainty, regression and bias arrive in plain words. There are no exercises, and the British examples can feel distant.

For anyone heading into data science, An Introduction to Statistical Learning is the widely assigned bridge from basic statistics to machine learning. The second edition covers regression, classification, decision trees, deep learning and survival analysis, and every chapter ends with a coding lab in R. The authors post the whole book as a free PDF, and a separate Python version came out later. It assumes comfort with algebra and some code, so it makes a poor first course.

Practice is the point of Statistics All-in-One For Dummies. Deborah Rumsey, a statistics professor at Ohio State, packs material from several of her Dummies guides into one volume, running from charts and averages through probability, confidence intervals and regression. Lessons go step by step, each chapter closes with a quiz, and buyers unlock more practice questions online. It's thick and a bit repetitive, since the merged books retell some basics.

Mario Triola's Essentials of Statistics trims his long-running Elementary Statistics to the topics a one-term college course covers. It needs only high school algebra, and its exercises lean on real data sets, from election results to medical studies. Each chapter shows how to do the work on a graphing calculator, Excel and other common programs. This is the sixth edition, online homework codes cost extra, and new print copies are getting scarce.

Psychology and education majors often meet Witte and Witte Statistics in their first required course. Robert and John Witte keep the math to arithmetic and algebra and spend their words on why each test works. Chapters run from tables and graphs through t-tests, analysis of variance, chi-square and tests that skip the usual assumptions, with review questions throughout. This 11th edition dates from 2017, and online homework costs extra.

Jim Frost spent years answering readers' questions on his Statistics By Jim website, and Jim Frost's Introduction to Statistics reads like those posts gathered into a course. It favors pictures and plain talk over formulas while covering graphs, averages, spread, distributions, probability, sampling and how to judge a study. It works well for self-study on the job. Hypothesis tests and regression live in his other books, so this one stops at the basics.

Naked Statistics is the book to hand a friend who swears they're bad at math. Charles Wheelan, a Dartmouth economist, uses jokes and everyday puzzles, such as the Monty Hall game show problem and how Netflix guesses what you'll like, to explain averages, correlation, polling and regression. Most formulas hide in short chapter appendices. It has no exercises, and some examples from its first printing in 2013 now look dated.

Comics carry the lessons in The Cartoon Guide to Statistics, drawn by Larry Gonick with statistician Woollcott Smith. Each page mixes gags with real formulas, worked examples and charts, moving from describing data through probability, sampling, confidence intervals, hypothesis tests and regression. It suits visual learners and anyone who needs a fast review before an exam. The book first appeared in 1993, so its references feel old, and some panels pack in dense algebra.