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William M. Briggs

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About Briggs
Briggs is an internationally reviled thoughtcriminal, listed as One Of The Top 7 Dangerous Minds by the Hague.
Let’s Try This Time Series Thing Again: Part I
Posted inStatistics

Let’s Try This Time Series Thing Again: Part I

This series originally began 5 February 2012. Part I, II, III, IV, V. We've gone on and on about how to think about time series, but we are having trouble…
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Posted inPhilosophy Statistics

On Corrections In Science

Somebody attributed to Max Planck, a constant1 source of wisdom, the saying that science advances funeral by funeral. This is a pithy condensation of his more famous quotation: A new…
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Posted inCulture Fun Statistics

Should Scientists Be Held Legally Responsible for Their Results?

That title is lifted from Popular Science's brief article. The idea is that scientists---as philosopher Christopher Essex reminded me, just like doctors and accountants and businessmen and engineers and everybody…
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Posted inStatistics

On Global Warming Apoplexy: Temperature Trends

It is a sure sign that Sanity has packed her bags and headed for the door when otherwise sober scientists begin slinging around terms like "denier" and "denialist." Language like…
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Posted inFun Statistics

How To Maximize The Chance Of Winning The Office Super Bowl Pool

Forget climatology. It's time for something really controversial. How to fill in those grid squares on the Super Bowl office pool. An example of one is shown below. The full…
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Posted inStatistics

Bad Astronomer Does Bad Statistics: That Wall Street Journal Editorial

Remember when I said how you shouldn't draw straight lines in time series and then speak of the line as if the line was the data itself? About how the…
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Posted inPhilosophy Statistics

All Of Statistics: Part III

(B) New data It might surprise you, but in classical (both frequentist and Bayesian) practice, if we expect to see new X, the procedure is almost always no different than…
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Posted inPhilosophy Statistics

All Of Statistics: Part II

(A) No new data (cont.) If we want to know how that data arose, and we are not satisfied by X itself, we need to propose a model---a fully causal…
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