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Significant fitness

Last September, in my efforts to recover from a knee injury, I hired a personal trainer.  When we made the original plan, it ended on 31 December 2021 and he added the slogan “New Year, New You” to the plan. It’s the new year and, thankfully, big progress. I just committed for another three months and I’m really looking forward to every single upcoming workout. It’s fun! However, like many new things, there are new insights and … surprise surprise, some are statistical.

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Significant fitness
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What is the use of lots of data when we don’t know what they mean?

There are lots of sources for data on Covid-19. Many of them just take data from government or hospital sources, and let you compare them however you want to. Others are a little more careful. Financial Times data journalists outline some of the problems:

Comparing the spread of coronavirus in different countries is difficult using the data being released by governments. Confirmed case counts depend heavily on the extent of countries’ very different testing regimes, so higher totals may simply reflect more testing.

Deaths are somewhat more reliable, but remain problematic because countries have different rules for what deaths to include in their official numbers. 

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What is the use of lots of data when we don’t know what they mean?
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Why is professional independence such a contentious issue?

The theme of professional independence in the production of official statistics is a subject that will never go away from the preoccupations of the international statistical community. It would seem that at any time somewhere in the world someone (usually a government) is trying to interfere against it. Last year, the attempt by the Trump administration to add a citizenship question to the 2020 US Population Census made the news in the US and worldwide, a decision more related to political considerations than to technical ones. In recent times, Argentina and Greece have also grabbed headlines around the world for altering figures in order to present a more favorable image of their economies, and a recent post on this blog raised awareness of a similar situation in Montenegro.

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Why is professional independence such a contentious issue?
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They are what they’re taught: The need for AI data curation ethics

Artificial intelligence (AI) refers to a bunch of computer algorithms used to build machines capable of carrying out tasks that typically require human intelligence. These machines learn particular tasks based on the data we generate. Similar to an old saying “We are what we eat,” the performance of an AI system depends on how and what we “teach” it.  Thus, the data collected and used are fundamental to training AI systems.

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They are what they’re taught: The need for AI data curation ethics
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Horror aequi …

…or fear of repeating a word is very common in the media. It’s a journalistic compulsion that is detrimental to clear communication and understanding – but easy to avoid.

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Horror aequi …
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How typical is a “median person”?

Last week, references to a “median person” showed up enough times in my life to spur me to write this post.  I think the use of an “average person” is still more popular, but this “median person” seems to be gaining popularity too.  Regardless, as attached to a person, the concept is essentially the same – it’s an appealing way to take a collection of averages (or medians) calculated for each of many measured characteristics and conceptually construct a new individual, as least hypothetically. The question that doesn’t get asked enough — Who, if anyone, does an individual constructed in this way actually “look” like?  

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How typical is a “median person”?
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There’s no evidence that …

More exposure means more opportunities to mutate. More selection pressure means more variants. This is certainly true for COVID-19 and it might also be true for political rhetoric. The many additional news conferences, press briefings and talk radio slots brought on by the pandemic are perfect conditions for breeding new sound bites and rhetorical tricks. Angry journalists and members of the public provide the selection pressure, weeding out the phrases that fall flat.

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There’s no evidence that …
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A year of statisticians reacting to the news

“We don’t exactly have a track record of selling most of our work to the world, do we?” wrote Janine Illian in her 18 May 2021 post, Found in TranslationThis blog is one way we, as a community, can share the value of statistical insights with the world, from making personal decisions to national policies. Just over a year ago, a suggestion within the ISI’s Committee on Public Voice led to the creation of a committee and then the start of this blog. The main purpose of the blog was for statisticians “to share our approach to reading the news, the questions we ask, and the conclusions we make (or don’t make).” 

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A year of statisticians reacting to the news
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Uncertainty is a funny thing: musings on wildfire and COVID

It’s a cliché at this point for news articles to compare COVID spread to a wildfire. But the start of meteorological summer in the northern hemisphere this past week coincides with the start of the north American wildfire season, and COVID still rages across the planet, so bear with me a moment for another take on this metaphor. 

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Uncertainty is a funny thing: musings on wildfire and COVID
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Found in translation

We were songbirds, we were Greek Gods

We were singled out by fate

We were quoted out of context – it was great.

Prefab Sprout, “Electric guitars”
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Found in translation