uncertainty
10 posts
People's interpretation of a chart can change if you use differents words to describe it, even if the data stays the same. Read More
The NYT election needles of uncertainty are back, and they’re about to go live (if they haven’t already). I’m not watching, but in case that’s your thing, there you go. It’s a little different this time around, because of the pandemic and mail-in voting. There’s no national needle this time. Instead, there are three needles for Florida, Georgia, and North Carolina, because they’re battleground states and the necessary data to...
To visualize uncertainty in election forecasts, Matthew Kay from Northwestern University used a Plinko metaphor. The height of each board is based on the distribution of the forecast, and each ball drop is a potential outcome. The animation plays to eventually shows a full distribution. See it in action. (And Kay made his R code available on GitHub.) Tags: election, Matthew Kay, Plinko, R, uncertainty
Look only at uncertainty and it can feel overwhelming. Look at just averages and it's not enough information. So, smoosh them together. Read More
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...
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....
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...
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...
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...
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...