Can a pet tortoise predict when it’s about to rain? That’s the somewhat unusual question posed by Conner Jackson, winner of Significance magazine’s Statistical Excellence Award for Early Career Writing. Jackson’s article, “Pietro the Weather Tortoise and the Pursuit of Soggy Bun Prevention,” leads the line-up of feature articles in the October 2021 issue of Significance.
In the same issue, there’s a focus on cybersecurity and how text analysis can be used to spot “phishing” attempts. And Part 3 of the magazine’s “History of the Data Economy” appears, with this latest installment telling the story of how social media sites became data economies in their own right.
There’s also an interview focusing on the UK statistical system’s response to COVID-19 and how it is preparing for what comes next, a discussion about data science standards, and an update to the story of “the lady tasting tea.”
Plus, have you ever wondered who was the best friend on the TV show Friends? Matthias Basner has, and he presents a quantitative analysis that attempts to answer that question.
Also in the October issue:
- Statistical inference allows researchers to learn about a population using only a sample of data from that population. But if it isn’t a random sample, inference becomes tricky or outright impossible, as Norbert Hirschauer, Sven Grüner, Oliver Mußhoff, Claudia Becker, and Antje Jantsch explain.
- Rob Gandy examines the contradictory adjectives used by the media to describe the same numbers in different contexts.
- Leighton Vaughan Williams introduces readers to “The Doomsday Argument.”
Access the digital version of Significance through ASA or RSS member portals or download and read the magazine on the go with our iOS and Android apps. Print issues will be mailed to subscribers soon.
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