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What book would you recommend for scientists who are not statisticians?

Clear delivery is most appreciated. As well as the explanation of the appropriate techniques and methods for typical tasks: time series analysis, presentation and aggregation of large data sets.

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    $\begingroup$ Could you be a little more precise? What type of analysis, in what context, etc. $\endgroup$ Jul 13, 2011 at 5:38
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    $\begingroup$ Statistics explained covers the basics using examples from the life sciences. The answers to this question may also contain recommendations that you'll find useful. $\endgroup$
    – MånsT
    Jun 15, 2012 at 13:59
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    $\begingroup$ Here is good list of books for non-statistician scientists. Most of them are probability related and some are readable for ones with a non-statistics background. HTH $\endgroup$
    – user31367
    Oct 11, 2013 at 0:23
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    $\begingroup$ Although this question has a high number of upvotes, I wonder if it's too broad for its own good - perhaps one might gauge so by the gap between votes for the question itself, and for its answers. The recommendations are a mish-mash, including books covering very specific areas of statistics, books which cover wider swathes of statistics but which are aimed at readers who work in very specific disciplines, books pitched at completely different difficulty levels and some answers lying closer to "popular science" genre. "Typical tasks" vary enormously between "scientists", broadly construed. $\endgroup$
    – Silverfish
    Apr 17, 2016 at 20:07
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    $\begingroup$ @Silverfish, I don't see any harm in letting this stay. It is CW; it is also well viewed & upvoted. It has clearly benefited a lot of people & there is no reason to suspect that wouldn't continue to be true. $\endgroup$ Apr 17, 2016 at 20:39

32 Answers 32

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Statistics

David Freedman, Robert Pisani, Roger Purves

Fourth edition: 2007, First edition: 1978

As an undergraduate studying philosophy, I was asked to analyze some data for a small study that I was working on with a physician. Needless to say, I found myself somewhat overwhelmed, but was able to get by by mimicking some old Stata code that a biostatistician friend had given me. The analysis turned out to be good enough to help get the study published, and I had suddenly become interested in this curious field of study called statistics.

The first book on statistics that I read was Statistics, by David Freedman and colleagues. What I liked most about it was its focus on explaining the fundamental concepts of statistical analysis (what do p-values actually mean, why is it important to visualize data, what does it mean for a test to be significant, etc) with concise and accurate language, but without too much mathematics. With that conceptual background, I found it much easier to go on to read more advanced literature with more advanced mathematics.

This book covers all topics covered in a first year statistics course, but does not cover time series or aggregation of large data sets. I feel it does a very good job at teaching a non-statistician how to think like a statistician. From there, adding new methods, like time series, should be relatively easy, and the non-statistician should be well on his way to becoming a life-long student of statistics.

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    $\begingroup$ +1 As someone who first learned stats from this book (right after the first edition came out :-), who has taught from it, and who has given many copies away to colleagues and clients, I can warmly recommend it. The exposition is marvelously clear. There's nothing outdated about the first edition, by the way: the third and fourth editions use more recent datasets but are otherwise about the same. This means the first (and now the third) editions are real bargains. (The second edition's ok, but it started to veer off course a little, a mistake that was corrected in subsequent editions.) $\endgroup$
    – whuber
    Jun 15, 2012 at 20:50
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    $\begingroup$ F P and P is a great book, It doesn't dumb things down and presents real problems. $\endgroup$
    – Peter Flom
    Sep 28, 2013 at 0:46
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The answer would most definitely depend on their discipline, the methods/techniques that they would like to learn and their existing mathematical/statistical abilities.

For example, economists/social scientists who want to learn about cutting edge empirical econometrics could read Angrist and Pischke's Mostly Harmless Econometrics. This is a non-technical book covering the "natural experimental revolution" in economics. The book only presupposes that they know what regression is.

But I think the best book on applied regression is Gelman and Hill's Data Analysis Using Regression and Multilevel/Hierarchical Models. This covers basic regression, multilevel regression, and Bayesian methods in a clear and intuitive way. It would be good for any scientist with a basic background in statistics.

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Peter Dalgaard's Introductory Statistics with R is a great book for some introductory statistics with a focus on the R software for data analysis.

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I'm going to assume some basic statistics knowledge and recommend:

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    $\begingroup$ The Statistical sleuth is used a the textbook on that great introductory course (there are 64 lectures in total) video.google.com/… $\endgroup$
    – Yorgos
    Jul 27, 2010 at 18:36
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    $\begingroup$ The first recommendation seems appropriate but Flury's book in not concise and deals with a special topic and is not a general introductory book on statistics. $\endgroup$ Jun 15, 2012 at 15:54
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    $\begingroup$ Oddly, the Flury book was linked to Jerry Dallal's excellent & free online test, The Little Handbook of Statistical Practice. I have corrected that, but leave the link to LHSP here--it's certainly a book I can highly recommend & it may be that @ars had intended to include it as well. $\endgroup$ Jul 28, 2012 at 3:04
  • $\begingroup$ That link is gone. What's the course called? $\endgroup$
    – quasi
    Sep 17, 2013 at 4:01
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Khan Academy has some nice introductory/beginner videos on statistics.

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A lot of Social Science / Psychology students with minimal mathematical background like Andy Field's book: Discovering Statistics Using SPSS. He also has a website that shares a lot of material.

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    $\begingroup$ That's a creepy website. $\endgroup$ Jun 6, 2014 at 14:29
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    $\begingroup$ I think Jeromy is correct. A lot of people like this book. Add to that (say) the comments of @whuber in the thread stats.stackexchange.com/questions/157217/… "Skimming pages here and there in the SPSS book provides insight into some of the really confused questions we get on this site: I think they must come from readers of that book. It is full of errors, misinformation, and outright confabulation." $\endgroup$
    – Nick Cox
    Jan 21, 2017 at 9:39
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Probably the best basic, get the big picture / ideas book is going to be:

Robert Abelson's Statistics as Principled Argument

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    $\begingroup$ That is a wonderful book (see my review but I think it is best as a companion volume. $\endgroup$
    – Peter Flom
    Sep 28, 2013 at 0:43
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Not intending to plug my book but it does seem to possibly apply. Last year I published a book with Wiley titled "The Essentials of Biostatistics for Physicians, Nurses and Clinicians". It is paperback and fairly concise 214 pages in total. It has the advantage for you that it emphasizes topics that are important in biological applications but may not be quite as concise as you would like to have for a 10 day self-learning course. "Introductory Statistics for Biology Students" 2nd Edtion by Trudy Watt and published by Chapman and Hall/CRC 1997 is another paperback that might be right for you. It is a little simpler than my book but does not include survival analysis which I consider to be a very important topic in biological studies (particularly clinical trials). Her book is 236 pages. I would also like to mention "The Cartoon Guide to Statistics" by Gonick. A humorous book but it also covers basic concepts very well and is exceptionally easy to read.

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    $\begingroup$ @Procrastinator. Thanks a lot. I really do apprciate your edits and those of MAcro, Huber and others. I will try to learn more and relieve some of the burden. $\endgroup$ Jul 24, 2012 at 19:07
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Statistics in Plain English is pretty good.

4.5 on Amazon, 11 reviews.

Explains ANOVA pretty well too.

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The Drunkard's Walk: How Randomness Rules Our Lives by Leonard Mlodinow is an excellent book for laypeople. Enjoyable and educational.

It might not be a textbook, but it makes you think about the world in the right way.

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It is a bit old, but I have found Chris Chatfield's book,

Statistics for Technology: A Course in Applied Technology

to be an excellent introduction.

It was how I first learned about statistics from a conceptual point of view.

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    $\begingroup$ only 3 reviews on Amazon...sketchy $\endgroup$ Dec 15, 2010 at 20:32
  • $\begingroup$ That's all? I'm surprised, cos it is a really good book. The same author wrote an excellent introduction to Time Series Analysis as well. $\endgroup$ Jan 5, 2011 at 19:41
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As a first introduction to the topic i liked Data Analysis: A Bayesian Tutorial.

For a deep and philosophical discussion of the underlying ideas of quantitative scientific reasoning i recommend Probability Theory: The Logic of Science. This book does not serve as a good introduction, though. It's only recommended for persons who want to know, why bayesian statistics is the way it is and/or are interested in a historic review of bayesian statistics.

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    $\begingroup$ I respectfully disagree regarding your second recommendation. Though certainly an interesting book, it is almost surely not the place to start for a non-statistician. Especially someone concerned about clear delivery. $\endgroup$
    – cardinal
    May 2, 2011 at 3:43
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    $\begingroup$ You're right, it's certainly not a good first read on the topic and not written in a concise way. Still, i thought for a scientist interested in how a consistent way of doing statistical analysis might be built, it makes an interesting read. But definitely not an introduction. I'll update my answer to reflect that. $\endgroup$ May 2, 2011 at 4:17
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    $\begingroup$ I agree with @cardinal but I'd add that the first book is also not a good as a first book on statistics -- in focuses solely on Bayesian approach, it is not comprehensive, it does not focus at the basic principles of statistics at all (it presents material quite selectively), and it requires some math background. Nonetheless it is a very nice book, just not a good as a "first book on statistics". $\endgroup$
    – Tim
    Jan 22, 2017 at 12:39
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So many wonderful recommendations! It's not quite what you asked for, but How to Lie with Statistics is short and quite wonderful. It doesn't directly teach the things you want, but it does help point out violation of assumptions and other flaws.

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    $\begingroup$ This could be helpful but not an introductory text on statistics. $\endgroup$ Jun 15, 2012 at 15:30
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The Flaw of Averages by Sam Savage.

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    $\begingroup$ A nice book and philosophical but not what the OOP is looking for. $\endgroup$ Jun 15, 2012 at 15:30
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"How to Tell the Liars from the Statisticians" by Hooke. I am fond of its way of explaining the concepts of statistics to laypersons.

As for explaining the motivations of statisticians, "The Lady Tasting Tea" is good reading.

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    $\begingroup$ I think these are both very nice books that would make excellent reading for the OP. But neither is a concise introductory text on statistics that the OP is requesting. $\endgroup$ Jun 15, 2012 at 15:43
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For the rudiments of statistics: http://www.bbc.co.uk/dna/h2g2/A1091350 and http://www.robertniles.com/stats/

For a good guide to data visualisation: http://www.perceptualedge.com/ - in particular, try the Graph Design IQ test at http://www.perceptualedge.com/files/GraphDesignIQ.html (requires Flash)

NB these are orthogonal - there are lots of statistics experts who are terrible at data visualisation, and vice versa.

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The following are text books I used for my MSEE coursework and research and I found them to be pretty good.

  1. Probability, Statistics and Random Processes for Engineers by Henry Stark and John W. Woods (Detailed explanation of concepts, good for Communications and Signal Processing people).
  2. Schaum's Outline of Probability, Random Variables and Random Processes by Hwei Hsu (Concise explanation of concepts, has a good amount of solved examples).
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Whitlock and Schluter The Analysis of Biological Data

3rd edition 2020 details at https://www.amazon.com/Analysis-Biological-Data-Michael-Whitlock/dp/131922623X

is an outstanding blend of statistics and science. You don't have to be a biologist (I'm certainly not) to understand and appreciate the examples. It's not only clear and sound, it's entertaining and enjoyable too.

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$\bullet$ "Biometry: The Principles and Practices of Statistics in Biological Research" by Robert R. Sokal and F. James Rohlf

$\bullet$ "Biostatistical Analysis" by Jerrold H. Zar
$\bullet$ "Primer of Biostatistics" by Stanton Glantz

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    $\begingroup$ Good recommendations here but the first two are not concise books. $\endgroup$ Jun 15, 2012 at 15:27
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I recently found Even You Can Learn Statistics to be pretty useful.

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I strongly recommend "Statistics for Experimenters: Design, Innovation, and Discovery , 2nd Edition" by Box, Hunter and Hunter. Must-read book for any scientist doing statistical analysis of their experiments. There's a companion R package (BHH2) as well.

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    $\begingroup$ This is a very good text but is not concise and emphasizes design rather than provide a general introduction to statistics. I think that many of the responses are getting away from the original question from the OP. $\endgroup$ Jun 15, 2012 at 15:47
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For years I have found the Engineering Statistics Handbook to be useful on a practical level.

It's freely available online.

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Gotelli and Ellison (2004) A Primer of Ecological Statistics

It's geared towards "Outdoor Science" (Ecology, Environmental Science, Biology) but the pedagogy is excellent. Anyone could benefit from it.

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I have recently had this website pointed out to me. It covers a number of books useful for new statisticians, with some targetted discussion of their various strengths and weaknesses, and a summary right at the bottom.

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    $\begingroup$ This discusses a lot of the books listed. It is a very nice link for the OP. It doesn't mention anything about books specifically directed to biologists though. $\endgroup$ Jun 15, 2012 at 15:51
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"Theoretical Statistics"
Keener, Robert W.
1st Edition., 2010, XVII, 538 p.
Hardcover, ISBN 978-0-387-93838-7

About the book...

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  • $\begingroup$ -1 How is this introductory and how does mentioning it answer the question? $\endgroup$ Jun 15, 2012 at 15:48
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    $\begingroup$ I am sorry that I upset you by my downvote. I thought it was appropriate to explain the reason for the downvote. The OP wants an introductory book and not something on theoratical statistics. If you don't answer the question you deserve a downvote. Also if it were a good book for beginners you should explain why. I gave an answer on June 15 and recommended 3 books appropriate for biologists physicians and nurses with an explanation as to why they are useful. The cartoon guide to statistics is very good for general audiences. $\endgroup$ Aug 3, 2012 at 4:55
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    $\begingroup$ But if you think that inspite of the title the book is valuable to scientists and add it to your answer I will retrack my downvote. My answer indicates that I did read and properly respond to the question. $\endgroup$ Aug 3, 2012 at 4:56
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    $\begingroup$ When I took Keener's theoretical statistics sequence in grad school this book hadn't been produced so we still used a "working" version of the book - it was very challenging but it was great. I think it approaches the subject a bit differently from from some of the "standard" theoretical statistics texts (e.g. Casella and Berger, Lehmann) and I think I prefer it. To be sure, this book requires a strong math background, although it is largely self contained. I'm glad to see its out now - I'll be sure to get a copy. $\endgroup$
    – Macro
    Aug 3, 2012 at 11:31
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    $\begingroup$ @Macro Have you seen the reviews this book has at amazon? One says that it's 'Plagued with confusing notation and exposition'. What is your opinion? $\endgroup$ Jul 4, 2014 at 1:26
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I would recommend: The statistical sleuth (Ramsey&Schafer) and biostatistical analysis (Zar).

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    $\begingroup$ Why do you recommend these books? $\endgroup$ Feb 4, 2014 at 7:55
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    $\begingroup$ We used the first book as a textbook; and one of the advantages is to teach you statistics by example. It is very good. And the second one is what I am reading and it is in detail to explain how statistics work. But for both books, there was one disadvantages: statistic software like R or others are not involved in the books. $\endgroup$
    – Lucas11
    Feb 6, 2014 at 3:40
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I'm really fond of the "for Dummies" series, and from the few pages I've read of it, Deborah J. Rumsey's "Statistics For Dummies" is a fine book for non-statisticians as well as Statisticians looking for a way to explain statistical concepts to non-statisticians.

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This link suggested many great books.

Besides that, I suggested: The Statistical Sleuth: A Course in Methods of Data Analysis. Following the examples in the book, many concepts become easier to understand.

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If you're to use SPSS, I'd recommend this book: Data Analysis for the Behavioral Sciences Using SPSS by Weinberg & Abramowitz. It is very well written and accessible. Note that it doesn't cover time-series, though.

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  • $\begingroup$ Finding a good introductory time series book is something I have dreamed of for years. Despite the fact that I have studied and done it for years, I don't think they exist. $\endgroup$
    – user54285
    Aug 7, 2020 at 21:17
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That'll depend very much on their background, but I found "Statistics in a Nutshell" to be pretty good.

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    $\begingroup$ I found Statistics in a Nutshell to be seriously flawed in terms of wrong/missing figures, mistakes in formulas, bad explanations and the book doesn't even have tables for critical values. This is especially bad at places where the authors write "and since the critical value for this is foo, this is significant", leaving the reader totally unclear about where this foo value comes from. The book does have a good intro section but should be edited eventually to make it good. Just look at the errata page for the book and be stunned at all the errors. $\endgroup$
    – xmjx
    Oct 17, 2010 at 9:07

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