Category Archives: statistics
“Tensors in Algebraic Statistics” (Elizabeth Gross)
Professor Elizabeth Gross. Some notes: Segre variety, about (These will be updated as I make progress through the talk.)
“Bayesian replication analysis” (by John Kruschke)
“… the ability to express [hypotheses] as distributions over parameters …” Bayesian estimation supersedes the t-test: (Also by Professor Kruschke.)
“Ten Fatal Flaws in Data Analysis” (Charles Kufs)
Professor Kufs has a fun book, Stats with Cats, and a blog. He also has a blog post tiled “Ten Fatal Flaws in Data Analysis” which, in general, I like. But the presentation has some shortcomings, too, which I note … Continue reading
A response to a post on RealClimate
(Updated 2342 EDT, 28 June 2019.) This is a response to a post on RealClimate which primarily concerned economist Ross McKitrick’s op-ed in the Financial Post condemning the geophysical community for disregarding Roger Pielke, Jr’s arguments. Pielke, in that link, … Continue reading
Cumulants and the Cornish-Fisher Expansion
“Consider the following.” (Bill Nye the Science Guy) There are random variables drawn from the same kind of probability distribution, but with different parameters for each. In this example, I’ll consider random variables , that is, each drawn from a … Continue reading
What’s good for each subgroup can be bad for the group: Simpson’s
Why? Simpson’s “paradox” or observation … There’s actually nothing odd about this. While interpretation depends upon the semantics of individual measurements, it should be expected that, at times, improving things for the overall group will mean as a matter of … Continue reading
California Marine Debris Prevention: Banning Plastic Bags is Not Enough
NOAA has a full page of videos on marine debris and how to prevent it. The state of California has a 2018 plan on preventing marine debris. Here are some highlights. There is a good deal more in the report, … Continue reading
Five Thirty Eight podcast: `Can Statistics solve gerrymandering?`
Great podcast, featuring Professor and geometer Moon Duchin, Nate Silver, and Galen Druke. If the link doesn’t work, listen from here or below: Professor Duchin has written extensively on this: M. Duchin, B. E. Tenner, “Discrete geometry for electoral geography”, … Continue reading
On bag bans and sampling plans
Plastic bag bans are all the rage. It’s not the purpose of this post to take a position on the matter. Before you do, however, I’d recommend checking out this: and especially this: (Note: My lovely wife, Claire, presents this … Continue reading
Repeating Bullshit
Originally posted on Open Mind:
Question: How does a dumb claim go from just a dumb claim, to accepted canon by the climate change denialati? Answer: Repetition. Yes, keep repeating it. If it’s contradicted by evidence, ignore that or insult…
A look at an electricity consumption series using SNCDs for clustering
(Slightly amended with code and data link, 12th January 2019.) Prediction of electrical load demand or, in other words, electrical energy consumption is important for the proper operation of electrical grids, at all scales. RTOs and ISOs forecast demand based … Continue reading
Series, symmetrized Normalized Compressed Divergences and their logit transforms
(Major update on 11th January 2019. Minor update on 16th January 2019.) On comparing things The idea of a calculating a distance between series for various purposes has received scholarly attention for quite some time. The most common application is … Continue reading
Why Americans and Britons work such long hours
Why Americans and Britons work such long hours.
667-per-cm.net, the Podcast: Episode 2, or Probability is Real.
This is the second installment of the Podcast here, hopefully with better sound quality.
Sampling: Rejection, Reservoir, and Slice
An article by Suilou Huang for catatrophe modeler AIR-WorldWide of Boston about rejection sampling in CAT modeling got me thinking about pulling together some notes about sampling algorithms of various kinds. There are, of course, books written about this subject, … Continue reading
A quick note on modeling operational risk from count data
The blog statcompute recently featured a proposal encouraging the use of ordinal models for difficult risk regressions involving count data. This is actually a second installment of a two-part post on this problem, the first dealing with flexibility in count … Continue reading
“All of Monsanto’s problems just landed on Bayer” (by Chris Hughes at Bloomberg)
See Chris Hughes’ article. Monsanto has touted Roundup (also known as Glyphosate but more properly as ) as a safe remedy for weed control, often in the taming of so-called “invasive species”. It’s used on playfields where children are exposed … Continue reading
Less evidence for a global warming hiatus, and urging more use of Bayesian model averaging in climate science
(This post has been significantly updated midday 15th February 2018.) I’ve written about the supposed global warming hiatus of 2001-2014 before: “‘Overestimated global warming over the past 20 years’ (Fyfe, Gillett, Zwiers, 2013)”, 28 August 2013 “Warming Slowdown?”, Azimuth, Part … Continue reading
Senn’s `… never having to say you are certain’ guest post from Mayo’s blog
via S. Senn: Being a statistician means never having to say you are certain (Guest Post) See also: E. Cai’s blog post “Applied Statistics Lesson of the Day – The Matched Pairs Experimental Design”, from February 2014 A. Deaton, N. … Continue reading
(thought of the day)
One accurate measurement is worth a thousand expert opinions. — Grace Murray Hopper Hat tip to Pat’s blog.
perceptions of likelihood
That’s from this Github repository, maintained by Zoni Nation, having this description. The original data are from a study by Sherman Kent at the U.S. CIA, and is quoted in at least once outside source discussing the problem. In addition … Continue reading
What are the odds of net zero?
What’s the Question? A question was posed by a colleague a couple of months ago: What are the odds of a stock closing at the same price it opened? I found the question interesting, because, at first, it appeared to … Continue reading
From Xian’s blog, “drivers are not interested in maths formulas”
via drivers are not interested in maths formulas
Confidence intervals and that IPCC: Why climate scientists need statistical help
At Andrew Gelman’s blog (Statistical Modeling, Causal Inference, and Social Science), Ben Goodrich makes the interesting observation in a length discussion about confidence intervals, how they should be interpreted, whether or not they have any socially redeeming value, und so … Continue reading
Disaster planning in a new climate, inland from the coasts
See Glynis Board’s “The New Normal: Super Storms Highlight Importance Of Disaster Planning”.
`Insurance companies should collect a carbon levy`
From Anthony J Webster and Richard H Clarke in Nature, “Insurance companies should collect a carbon levy”: Governments juggle too many interests to drive global action on climate change. But the insurance industry is ideally placed. With annual premiums amounting … Continue reading
A “capacity for sustained muddle-headedness”
Hat tip to Paul Lauenstein, and his physician brother, suggesting the great insights of the late Dr Larry Weed: Great lines, great quotes, a lot of humor: “… a tolerance of ambiguity …” “Y’know, Pavlov said you must teach a … Continue reading
`Exxon Shareholders Approve Climate Resolution: 62% Vote for Disclosure’
Flash from InsideClimate News: ExxonMobil shareholders voted Wednesday to require the world’s largest oil and gas company to report on the impacts of climate change to its business—defying management, and marking a milestone in a 28-year effort by activist investors. … Continue reading
Dikran Marsupial’s excellent bit on hypothesis testing applied to climate, or how it should be applied, if at all
Frankly, I wish some geophysicists and climate scientists wrote more as if they thoroughly understood this, let alone deniers to try to discredit climate disruption. See “What does statistically significant actually mean?”. Of course, while statistical power of a test … Continue reading