andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-965 knowledge-graph by maker-knowledge-mining
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Introduction: Aleks points me to this new tool from Wojciech Gryc. Right now I save my graphs as pdfs or pngs and then upload them to put them on the web. I expect I’ll still be doing this for awhile—I like having full control of what my graphs look like—but Gryc’s default plots might be useful for lots of people making their analyses more accessible. Here’s an example: x = rnorm(30) y = rnorm(30) wv.plot(x, y, "~/Desktop/scatterplot", height=300, width=300, xlim=c(-2.5,2.5), ylim=c(-2.5,2.5), xbreaks=c(0), ybreaks=c(0))
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3 I expect I’ll still be doing this for awhile—I like having full control of what my graphs look like—but Gryc’s default plots might be useful for lots of people making their analyses more accessible. [sent-3, score-1.612]
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Introduction: Aleks points me to this new tool from Wojciech Gryc. Right now I save my graphs as pdfs or pngs and then upload them to put them on the web. I expect I’ll still be doing this for awhile—I like having full control of what my graphs look like—but Gryc’s default plots might be useful for lots of people making their analyses more accessible. Here’s an example: x = rnorm(30) y = rnorm(30) wv.plot(x, y, "~/Desktop/scatterplot", height=300, width=300, xlim=c(-2.5,2.5), ylim=c(-2.5,2.5), xbreaks=c(0), ybreaks=c(0))
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Introduction: Aleks pointed me to this .
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Introduction: Aleks sent me this (I’m not sure from where):
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Introduction: Aleks points me to this new tool from Wojciech Gryc. Right now I save my graphs as pdfs or pngs and then upload them to put them on the web. I expect I’ll still be doing this for awhile—I like having full control of what my graphs look like—but Gryc’s default plots might be useful for lots of people making their analyses more accessible. Here’s an example: x = rnorm(30) y = rnorm(30) wv.plot(x, y, "~/Desktop/scatterplot", height=300, width=300, xlim=c(-2.5,2.5), ylim=c(-2.5,2.5), xbreaks=c(0), ybreaks=c(0))
2 0.80090028 795 andrew gelman stats-2011-07-10-Aleks says this is the future of visualization
Introduction: Here . My reaction was, It’s cute how the bars move but why is this the future? Aleks replied: Integrated in the browser, works on any device, requires no software installation. Here are more examples, for maps.
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Introduction: Just in time for the hot weather . . . Aleks points me to this link to a graph of % check-ins at NYC ice cream shops plotted against temperature in 2011. Aleks writes, “interesting how the ice cream response lags temperature in spring/fall but during the summer, the response is immediate.” This graph is a good starting point but I think more could be done, both in the analysis and purely in the graphics. Putting the two lines together like this with a fixed ratio is just too crude a tool. A series of graphs done just right could show a lot, I think!
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Introduction: Aleks sent me this (I’m not sure from where):
5 0.77094036 428 andrew gelman stats-2010-11-24-Flawed visualization of U.S. voting maybe has some good features
Introduction: Aleks points me to this attractive visualization by David Sparks of U.S. voting. On the plus side, the pictures and associated movie (showing an oddly horizontally-stretched-out United States) are pretty and seem to have gotten a bit of attention–the maps have received 31 comments, which is more than we get on almost all our blog entries here. On the minus side, the movie is misleading. In many years it shows the whole U.S. as a single color, even when candidates from both parties won some votes. The text has errors too, for example the false claim that the South favored a Democratic candidate in 1980. The southern states that Jimmy Carter carried in 1980 were Georgia and . . . that’s it. But, as Aleks says, once this tool is out there, maybe people can use it to do better. It’s in that spirit that I’m linking. Ya gotta start somewhere. Also, this is a good example of a general principle: When you make a graph, look at it carefully to see if it makes sense!
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Introduction: Chris Wiggins sends along this . It’s a meetup at Davis Auditorium, CEPSR Bldg, Columbia University, on Wed 10 Nov (that’s tomorrow! or maybe today! depending on when you’re reading this), 6-8pm.
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Introduction: WeatherSpark : prediction and observation quantiles, historic data, multiple predictors, zoomable, draggable, colorful, wonderful: Via Jure Cuhalev .
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Introduction: Aleks points me to this new tool from Wojciech Gryc. Right now I save my graphs as pdfs or pngs and then upload them to put them on the web. I expect I’ll still be doing this for awhile—I like having full control of what my graphs look like—but Gryc’s default plots might be useful for lots of people making their analyses more accessible. Here’s an example: x = rnorm(30) y = rnorm(30) wv.plot(x, y, "~/Desktop/scatterplot", height=300, width=300, xlim=c(-2.5,2.5), ylim=c(-2.5,2.5), xbreaks=c(0), ybreaks=c(0))
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