Statistics in a nutshell
by Sarah Boslaugh · first published 2008
70% recommend10% neutral20% critical
Why HN recommends it
Readable reference that also lays out the underlying concepts, not just formulas; well structured for looking things up, and a good fit for practitioners who want a practical stats refresher or a bridge to textbooks.
Summarised by Claude from recommending comments
An introduction to statistics covers the concepts of measurement and probability theory, correlation, inferential techniques, and statistical analysis.
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Mentions per year
What Hacker News says
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…Make sure it explains things really well. The best person to teach someone is a beginner, because they understand the beginner's perspective. So you are in a unique position to create this. O'Reillys statistics in a nutshell is a good reference* book, but not quite a textbook. Here you go. Including my refid. http://www.amazon.com/gp/product/0596510497?ie=UTF8&tag=... *True masters have beginner perspectives, so they are…
on “Ask HN: Statistics for hackers?” ↗I really liked O'Reilly's Statistics in a Nutshell; it's readable, it's well structured if you need to look up something, but it isn't just a toolbox, it also spends the time to lay down the concepts and put things in perspective.
on “Free book on Statistics for Programmers” ↗O'Reilly's Statistics In a Nutshell is quite good as both a textbook and a reference. I'm (slowly) working through it on my own.
on “For Today’s Graduate, Just One Word: Statistics” ↗Project Euler is a fun way to motivate yourself to learn some algorithms, number theory, and a few other math topics, by solving programming puzzles: http://projecteuler.net/ O'Reilly's Statistics in a Nutshell is a good stats textbook and reference, has some good exercises to be done in R (or S or Matlab), and is generally more programming-oriented than most statistics treatments. http://oreilly.com/catalog/9780596510497/…
on “Ask HN: Learn math faster w/ computers” ↗Have you looked at "Statistics in a Nutshell"? http://shop.oreilly.com/product/0636920023074.do
on “The Probability and Statistics Cookbook” ↗Depends on what you are looking for. If you are looking for something that is accessible and practical I'd go with Statistics in a Nutshell from O'Reily. If you are looking for something a bit more theoretical I'd recommend Wackerly's Mathematical Statistics.
on “Ask HN: What are some top-shelf statistics textbooks?” ↗For stats, I found the Stats for Dummies and Statistics in a Nutshell were great resources to refresh and review. It's easier to relearn some of this stuff when you know what you don't know!
on “No bullshit guide to linear algebra – v2” ↗Not a textbook, but I found “Statistics in a Nutshell” to be a good refresher for my long dormant stats knowledge.
on “Ask HN: What are your favorite statistics and probability textbooks?” ↗I’d probably sample it randomly yes. Crap jokes aside, I mostly use Statistics In A Nutshell. It’s pretty ok. I say that as a member of the RSS for 30 odd years.
on “Ask HN: Would you read a statistics textbook?” ↗…was hooked from the first sentence: "Probability is a mathematical language for quantifying uncertainty." That one sentence makes the concept clear in a way that the entire chapter on probability from "Statistics in a Nutshell" (http://www.amazon.com/Statistics-Nutshell-Sarah-Boslaugh/dp/...) did not. I'm not someone who thrives on theorems and proofs, I thrive on concepts. And I found this book dense with clear explanations…
on “All of Statistics, by Larry Wassserman (2013) [pdf]” ↗…was hooked from the first sentence: "Probability is a mathematical language for quantifying uncertainty." That one sentence makes the concept clear in a way that the entire chapter on probability from "Statistics in a Nutshell" (http://www.amazon.com/Statistics-Nutshell-Sarah-Boslaugh/dp/...) did not." --> "Statistics in a Nutshell" got added to list 20 of year 2016
on “Show HN: Top books mentioned in comments on Hacker News” ↗Anyone read the Data Science Design Manual by Skienna and find it useful? Curious if it’s a good intro source or something like Statistics in a Nutshell
on ““Foundations of Data Science”, Free Book by Hopcroft and Kannan [pdf]” ↗