Name: The Art of Statistics
ISBN: 9781541618510

The Art of Statistics

The definitive guide to statistical thinking Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence -- and even more so if we hope to participate in the future, rather than being simple bystanders. In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems -- it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and -- perhaps even more importantly -- we learn how to responsibly interpret the answers we receive. Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.

What Hacker News says

rramadassFeb 2026

> Especially for probability and statistics.

For the general reader, two books by David Spiegelhalter (https://en.wikipedia.org/wiki/David_Spiegelhalter) are relevant here;

1) The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck.

2) The Art of Statistics: Learning from Data.

And of course, all the books by Nassim Taleb.

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hktApr 2022

JSTOR, Cochrane reviews, trade journals, and live blogs. Mostly I've gravitated away from "news" to sources.

Picking good sources is hard, though. Generally I find it has to be the case that specialists writing about their specialism are the people who knowledge originates with, even when it isn't lay people.

Where curation is worth it is in reviews. The London Review of Books will introduce a wide array of new literature to me and prepare the ground for approaching those books by explaining the content and critically analysing it.

Statistical literacy also helps - for this I've read David Spiegelhalter's Art of Statistics, which is for the lay reader.

News-wise, single generally credible sources are hard to come by. The Guardian does good live blogs, especially on UK parliamentary debates. The New York Times has a solid but anglocentric newsgathering operation, but tragically partisan opinion. Le Monde Diplomatique is good for international stuff from a francophone perspective.

tl;dr, navigate institutions, not search engines. Institutions are in effect communities with a culture that guards against rot algorithms can't perceive.

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r4umDec 2021

I highly recommend The Art of Statistics.

https://www.goodreads.com/book/show/43722897-the-art-of-stat...

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mrslaveMar 2021

Darrell Huff - How To Lie With Statistics[0]. And the first chapter or two of David Spiegelhalter - The Art of Statistics[1] has a good example of absolute vs relative rates/probabilities with respect to medicine. Pretty basic an important issue to understand.

[0] https://www.goodreads.com/book/show/51291.How_to_Lie_with_St... [1] https://www.goodreads.com/book/show/43722897-the-art-of-stat...

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nickcwFeb 2021

The sad thing is that the team responsible for this bit of machine learning are probably very proud of their 99% accurate algorithm.

It probably *is* 99% accurate - there is a lot of fraudulent activity online.

That 1% false positive rate really hurts though, destroying people's livelihoods.

I think that people developing machine learning models sometimes don't think about the consequences of the false positives enough.

There is a great section in David Spiegelhalter's book The Art of Statistics which got me thinking about this.

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troelsSteeginMay 2020

For up to date work, see the MU Collective [0]: "We are a cross-institution research lab working at the intersection of information visualization and uncertainty communication. Our mission is to improve both experts' and lay people's abilities to reason about data through visual representations that align with how people think. Topics we like include sampling-oriented uncertainty visualizations, interactive visualization for thinking about priors, multiple views, and Bayesian statistics.

MU Collective is directed by Jessica Hullman (Northwestern University) and Matt Kay (University of Michigan)"

Hullman is also usefully active on twitter [1]. There's lots going on in this area.

The posted article links through to "Understanding Uncertainty", [2], which has a mission of improving the public's understanding of uncertainty but appears to be a lapsed project. One member of the project team is David Spiegelhalter, who is still writing. His book "The Art of Statistics" is an excellent book on the craft of inference.

[0] https://mucollective.northwestern.edu/ [1] https://twitter.com/JessicaHullman [2] https://understandinguncertainty.org/

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