uncertainty

60 posts
Choose your own election outcome

The election is full of what-ifs, and the result changes depending on which direction they take. Josh Holder and Alexander Burns for The New York Times use a pair of circular Voronoi diagrams and draggable bubbles so that you can test the what-ifs. Contrast this with NYT’s 2012 graphic showing all possible paths. While the 2012 graphic shows you the big picture, the 2020 interactive places more weight on individual...

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FiveThirtyEight launches 2020 election forecast

The election is coming. FiveThirtyEight just launched their forecast with a look at the numbers from several angles. Maps, histograms, beeswarms, and line charts, oh my. There is also a character named Fivey Fox, which is like Microsoft’s old Clippy providing hints and tips to interpret the results. One thing you’ll notice, and I think newsrooms have been working towards this, there’s a lot of uncertainty built into the views....

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Understanding Covid-19 statistics

For ProPublica, Caroline Chen, with graphics by Ash Ngu, provides a guide on how to understand Covid-19 statistics. The guide offers advice on interpreting daily changes, spotting patterns over longer time frames, and finding trusted sources. Most importantly: Even if the data is imperfect, when you zoom out enough, you can see the following trends pretty clearly. Since the middle of June, daily cases and hospitalizations have been rising in...

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How experts use disease modeling to help inform policymakers

Harry Stevens and John Muyskens for The Washington Post put you in the spot of an epidemiologist receiving inquiries from policymakers about what might happen: Imagine you are an epidemiologist, and one day the governor sends you an email about an emerging new disease that has just arrived in your state. To avoid the complexities of a real disease like covid-19, the illness caused by the novel coronavirus, we have...

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Not making Covid-19 charts

Will Chase, who specialized in visualization for epidemiological studies in grad school, outlined why he won’t make charts showing Covid-19 data: So why haven’t I joined the throng of folks making charts, maps, dashboards, trackers, and models of COVID19? Two reasons: (1) I dislike reporting breaking news, and (2) I believe this is a case of “the more you know, the more you realize you don’t know” (a.k.a. the Dunning-Kruger...

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Possible coronavirus deaths compared against other causes

Based on estimates from public health researcher James Lawler, The Upshot shows the range of coronavirus deaths, given variable infection and fatality rate. Adjust with the sliders and see how the death count (over a year) compares against other major causes of death: Dr. Lawler’s estimate, 480,000 deaths, is higher than the number who die in a year from dementia, emphysema, stroke or diabetes. There are only two causes of...

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Statistical uncertainty as certainty

Mark Rober, who is having a good run of science and engineering videos on YouTube, posted a short note on how he embraces statistical uncertainty: As humans we are really good at using hindsight bias to convince ourselves we are more in control of things than we really are. For example, if you give 1024 people a coin and give them 10 tries to get as many tails as possible,...

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Useful and not so useful Statistics

Hannah Fry, for The New Yorker, describes the puzzle of Statistics to analyze general patterns used to make decisions for individuals: There is so much that, on an individual level, we don’t know: why some people can smoke and avoid lung cancer; why one identical twin will remain healthy while the other develops a disease like A.L.S.; why some otherwise similar children flourish at school while others flounder. Despite the...

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Gallery of uncertainty visualization methods

It must be uncertainty month and nobody told me. For Scientific American, Jessica Hullman briefly describes her research in uncertainty visualization with a gallery of options from worst to best. Tags: Jessica Hullman, Scientific American, uncertainty

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What that hurricane map means

For The New York Times, Alberto Cairo and Tala Schlossberg explain the cone of uncertainty we often see in the news when a hurricane approaches. People often misinterpret the graphic: The cone graphic is deceptively simple. That becomes a liability if people believe they’re out of harm’s way when they aren’t. As with many charts, it’s risky to assume we can interpret a hurricane map correctly with just a glance....

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