“Holy crap – an actual book!”

You’ll find links to Cathy O’Neil’s important book in the Blogroll here, as well as a link to reviews of it.

I have not read it yet. While I have pre-ordered it, it’s not available. I have read the reviews, all favorable. I suspect it expresses a lot of concern that statisticians, including myself, have long expressed regarding “data mining” (data dredging), and inferences derived from “big data”, including a lack of concern about the quality of the data, forgetting about cleaning, and whether or not, despite the size of a dataset, there is enough data to warrant a strong estimate or inference in a particular case.

These arguments have been made by many, like Simply Statistics‘ “Why big data is in trouble: they forgot about applied statistics” from 2014. Or Bajorski’s “Applied Statistics Comes to the Rescue of Big Data”. And the wave of emphasis upon pure machine learning methods of late does not help: These obfuscate and confound, making it harder to understand what’s really going on.

Anyway, I very much look forward to reading the book!

mathbabe

Yo, everyone! The final version of my book now exists, and I have exactly one copy! Here’s my editor, Amanda Cook, holding it yesterday when we met for beers:

20160809_161608

Here’s my son holding it:

20160809_161558 He’s offered to become a meme in support of book sales.

Here’s the back of the book, with blurbs from really exceptional people:

20160810_074117

In other exciting book news, there’s a review by Richard Beales from Reuter’s BreakingViews, and it made a list of new releases in Scientific American as well.

Endnote:

I want to apologize in advance for all the book news I’m going to be blogging, tweeting, and otherwise blabbing about. To be clear, I’ve been told it’s my job for the next few months to be a PR person for my book, so I guess that’s what I’m up to. If you come here for ideas and are turned off by cheerleading, feel…

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About hypergeometric

See http://www.linkedin.com/in/deepdevelopment/ and http://667-per-cm.net
This entry was posted in American Association for the Advancement of Science, Buckminster Fuller, business, citizen science, citizenship, civilization, complex systems, confirmation bias, data science, data streams, deep recurrent neural networks, denial, economics, education, engineering, ethics, evidence, Internet, investing, life purpose, machine learning, mathematical publishing, mathematics, mathematics education, maths, moral leadership, multivariate statistics, numerical software, numerics, obfuscating data, organizational failures, politics, population biology, prediction, prediction markets, privacy, quantitative biology, quantitative ecology, rationality, reason, reasonableness, rhetoric, risk, Schnabel census, smart data, sociology, statistical dependence, statistics, the right to be and act stupid, the right to know, the value of financial assets, transparency, UU Humanists. Bookmark the permalink.

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