andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-1862 knowledge-graph by maker-knowledge-mining
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Introduction: Hamdan Azhar writes: I came across this graphic of vaccine-attributed decreases in mortality and was curious if you found it as unattractive and unintuitive as I did. Hope all is well with you! My reply: All’s well with me. And yes, that’s one horrible graph. It has all the problems with a bad infographic with none of the virtues. Compared to this monstrosity, the typical USA Today graph is a stunning, beautiful masterpiece. I don’t think I want to soil this webpage with the image. In fact, I don’t even want to link to it.
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3 Compared to this monstrosity, the typical USA Today graph is a stunning, beautiful masterpiece. [sent-6, score-0.505]
4 I don’t think I want to soil this webpage with the image. [sent-7, score-0.391]
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same-blog 1 1.0000001 1862 andrew gelman stats-2013-05-18-uuuuuuuuuuuuugly
Introduction: Hamdan Azhar writes: I came across this graphic of vaccine-attributed decreases in mortality and was curious if you found it as unattractive and unintuitive as I did. Hope all is well with you! My reply: All’s well with me. And yes, that’s one horrible graph. It has all the problems with a bad infographic with none of the virtues. Compared to this monstrosity, the typical USA Today graph is a stunning, beautiful masterpiece. I don’t think I want to soil this webpage with the image. In fact, I don’t even want to link to it.
2 0.14092988 1096 andrew gelman stats-2012-01-02-Graphical communication for legal scholarship
Introduction: Following my talk on infovis and statistical graphics at the Empirical Legal Studies conference , Dan Kahan writes: The legal academy, which is making strides toward sensible integration of a variety of empirical methods into its scholarship, is horribly ignorant of the utility of graphic reporting of data, a likely influence of the formative influence that econometric methods has exerted on expectations and habits of mind among legal scholars. Lee Epstein has written a pair of wonderful articles on graphic reporting – 1. Epstein, L., Martin, A. & Boyd, C. On the Effective Communication of the Results of Empirical Studies, Part II. Vand. L. Rev. 60, 798-846 (2007). 2. Epstein, L., Martin, A. & Schneider, M. On the Effective Communication of the Results of Empirical Studies, Part I. Vand. L. Rev. 59, 1811-1871 (2007). – but her efforts haven’t gotten the attention they deserve, and reinforcement, particularly at a venue like CELS is very important. But the main issue there
3 0.14002302 572 andrew gelman stats-2011-02-14-Desecration of valuable real estate
Introduction: Malecki asks: Is this the worst infographic ever to appear in NYT? USA Today is not something to aspire to. To connect to some of our recent themes , I agree this is a pretty horrible data display. But it’s not bad as a series of images. Considering the competition to be a cartoon or series of photos, these images aren’t so bad. One issue, I think, is that designers get credit for creativity and originality (unusual color combinations! Histogram bars shaped like mosques!) , which is often the opposite of what we want in a clear graph. It’s Martin Amis vs. George Orwell all over again.
4 0.13863762 301 andrew gelman stats-2010-09-28-Correlation, prediction, variation, etc.
Introduction: Hamdan Azhar writes: I [Azhar] write with a question about language in the context of statistics. Consider the three statements below. a) Y is significantly associated (correlated) with X; b) knowledge of X allows us to account for __% of the variance in Y; c) Y can be predicted to a significant extent given knowledge of X. To what extent are these statements equivalent? Much of the (non-statistical) scientific literature doesn’t seem to distinguish between these notions. Is this just about semantics — or are there meaningful differences here, particularly between b and c? Consider a framework where X constitutes a predictor space of p variables (x1,…,xp). We wish to generate a linear combination of these variables to yield a score that optimally correlates with Y. Can we substitute the word “predicts” for “optimally correlates with” in this context? One can argue that “correlating” or “accounting for variance” suggests that we are trying to maximize goodness-of-fit (i
5 0.12582742 722 andrew gelman stats-2011-05-20-Why no Wegmania?
Introduction: A colleague asks: When I search the web, I find the story [of the article by Said, Wegman, et al. on social networks in climate research, which was recently bumped from the journal Computational Statistics and Data Analysis because of plagiarism] only on blogs, USA Today, and UPI. Why is that? Any idea why it isn’t reported by any of the major newspapers? Here’s my answer: 1. USA Today broke the story. Apparently this USA Today reporter put a lot of effort into it. The NYT doesn’t like to run a story that begins, “Yesterday, USA Today reported…” 2. To us it’s big news because we’re statisticians. [The main guy in the study, Edward Wegman, won the Founders Award from the American Statistical Association a few years ago.] To the rest of the world, the story is: “Obscure prof at an obscure college plagiarized an article in a journal that nobody’s ever heard of.” When a Harvard scientist paints black dots on white mice and says he’s curing cancer, that’s news. When P
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20 0.07896468 21 andrew gelman stats-2010-05-07-Environmentally induced cancer “grossly underestimated”? Doubtful.
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Introduction: Hamdan Azhar writes: I came across this graphic of vaccine-attributed decreases in mortality and was curious if you found it as unattractive and unintuitive as I did. Hope all is well with you! My reply: All’s well with me. And yes, that’s one horrible graph. It has all the problems with a bad infographic with none of the virtues. Compared to this monstrosity, the typical USA Today graph is a stunning, beautiful masterpiece. I don’t think I want to soil this webpage with the image. In fact, I don’t even want to link to it.
2 0.78901303 832 andrew gelman stats-2011-07-31-Even a good data display can sometimes be improved
Introduction: When I first saw this graphic, I thought “boy, that’s great, sometimes the graphic practically makes itself.” Normally it’s hard to use lots of different colors to differentiate items of interest, because there’s usually not an intuitive mapping between color and item (e.g. for countries, or states, or whatever). But the colors of crayons, what could be more perfect? So this graphic seemed awesome. But, as they discovered after some experimentation at datapointed.net there is an even BETTER possibility here. Click the link to see. Crayola Crayon colors by year
Introduction: Ben Hyde sends along this appealing image by Michael Paukner, which represents a nearly perfect distillation of “infographics”: Here are some of the comments on the linked page: Rather than redrawing the picture to make the lines more clear, I’d say: leave the graphic as is, and have a link to a set of statistical graphs that show where the different sorts of old trees are and what they look like. Let’s value the above image for its clean look and its clever Christmas-tree design, and once we have it, take advantage of viewers’ interest in the topic to show them more. P.S. See my comment below which I think further illuminates the appeal of this particular tree.
4 0.66835815 2154 andrew gelman stats-2013-12-30-Bill Gates’s favorite graph of the year
Introduction: Under the subject line “Blog bait!”, Brendan Nyhan points me to this post at the Washington Post blog: For 2013, we asked some of the year’s most interesting, important and influential thinkers to name their favorite graph of the year — and why they chose it. Here’s Bill Gates’s. Infographic by Thomas Porostocky for WIRED. “I love this graph because it shows that while the number of people dying from communicable diseases is still far too high, those numbers continue to come down. . . .” As Brendan is aware, this is not my favorite sort of graph, it’s a bit of a puzzle to read and figure out where all the pieces fit in, also weird stuff going on like 3-D effects and the big space taken up by those yellow and green borders, as well as tricky things like understanding what some of those little blocks are, and perhaps the biggest question, what is the definition of an “untimely death.” But, as often is the case, the defects of the graph form a statistical perspective can
Introduction: Jonathan Robinson writes: I’m a survey researcher who mostly does political work, but I also have a strong interest in economics. I have a question about this graph you commonly see in the economics literature. It is of a concept called the Beveridge Curve [recently in the newspaper here ]. It is one of the more interesting concepts in labor economics, relating the vacancy rate in jobs to the unemployment rate. A good primer is here . However, despite being one of the more interesting concepts in economics, the way it is displayed visually is nothing short of atrocious: These graphs are nothing short of unreadable and pretty much the standard (Brad Delong has linked to this graph above and it can appear like this in publication as well). I’ve only really seen one representation of the curve that is more clear than this and it is at this link : Do you have any ideas of any way of making these graphs more readable? I like the second Cleveland Fed graph, but I ha
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1 0.96235609 876 andrew gelman stats-2011-08-28-Vaguely related to the coke-dumping story
Introduction: Underground norms from Jay Livingston. P.S. The Coke story is here (and is followed up in the comments).
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Introduction: The R language is definitely going mainstream:
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Introduction: When I first saw this graphic, I thought “boy, that’s great, sometimes the graphic practically makes itself.” Normally it’s hard to use lots of different colors to differentiate items of interest, because there’s usually not an intuitive mapping between color and item (e.g. for countries, or states, or whatever). But the colors of crayons, what could be more perfect? So this graphic seemed awesome. But, as they discovered after some experimentation at datapointed.net there is an even BETTER possibility here. Click the link to see. Crayola Crayon colors by year
4 0.91363138 1820 andrew gelman stats-2013-04-23-Foundation for Open Access Statistics
Introduction: Now here’s a foundation I (Bob) can get behind: Foundation for Open Access Statistics (FOAS) Their mission is to “promote free software, open access publishing, and reproducible research in statistics.” To me, that’s like supporting motherhood and apple pie ! FOAS spun out of and is partially designed to support the Journal of Statistical Software (aka JSS , aka JStatSoft ). I adore JSS because it (a) is open access, (b) publishes systems papers on statistical software, (c) has fast reviewing turnaround times, and (d) is free for authors and readers. One of the next items on my to-do list is to write up the Stan modeling language and submit it to JSS . As a not-for-profit with no visible source of income, they are quite sensibly asking for donations (don’t complain — it beats $3K author fees or not being able to read papers).
5 0.88968688 2101 andrew gelman stats-2013-11-15-BDA class 4 G+ hangout on air is on air
Introduction: Here. And here ‘s the backstory. P.S. The damn mike was muted most of the time. Something always goes wrong!
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