Category: Statistical graphics

Perhaps you could try a big scatterplot with one dot per dataset?

Joe Nadeau writes: We are studying variation in both means and variances in metabolic conditions. We have access to nearly 200 datasets that involve a range of metabolic traits and vary in sample size, mean effects, and variance. Some traits differ in mean but not variance, others in variance but not mean, still others in […]

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“Fudged statistics on the Iraq War death toll are still circulating today”

Mike Spagat shares this story entitled, “Fudged statistics on the Iraq War death toll are still circulating today,” which discusses problems with a paper published in a scientific journal in 2006, and errors that a reporter inadvertently included in a recent news article. Spagat writes: The Lancet could argue that if [Washington Post reporter Philip] […]

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How to graph a function of 4 variables using a grid

This came up in response to a student’s question. I wrote that, in general, you can plot a function y(x) on a simple graph. You can plot y(x,x2) by plotting y vs x and then having several lines showing different values of x2 (for example, x2=0, x2=0.5, x2=1, x2=1.5, x2=2, etc). You can plot y(x,x2,x3,x4) […]

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Don’t get fooled by observational correlations

Gabriel Power writes: Here’s something a little different: clever classrooms, according to which physical characteristics of classrooms cause greater learning. And the effects are large! Moving from the worst to the best design implies a gain of 67% of one year’s worth of learning! Aside from the dubiously large effect size, it looks like the […]

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Against Arianism 2: Arianism Grande

“There’s the part you’ve braced yourself against, and then there’s the other part” – The Mountain Goats My favourite genre of movie is Nicole Kidman in a questionable wig. (Part of the sub-genre founded by Sarah Paulson, who is the patron saint of obvious wigs.) And last night I was in the same room* as […]

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Who spends how much, and on what?

Nathan Yau (link from Dan Hirschman) constructed the above excellent visualization of data from the Consumer Expenditure Survey. Lots of interesting things here. The one thing that surprises me is that people (or maybe it’s households) making more than $200,000 only spent an average of $160,000. I guess the difference is taxes, savings (but not […]

The post Who spends how much, and on what? appeared first on Statistical Modeling, Causal Inference, and Social Science.

Who spends how much, and on what?

Nathan Yau (link from Dan Hirschman) constructed the above excellent visualization of data from the Consumer Expenditure Survey. Lots of interesting things here. The one thing that surprises me is that people (or maybe it’s households) making more than $200,000 only spent an average of $160,000. I guess the difference is taxes, savings (but not […]

The post Who spends how much, and on what? appeared first on Statistical Modeling, Causal Inference, and Social Science.

What’s gonna happen in the 2018 midterm elections?

Following up on yesterday’s post on party balancing, here’s a new article from Joe Bafumi, Bob Erikson, and Chris Wlezien giving their predictions for November: We forecast party control of the US House of Representatives after the 2018 midterm election. First, we model the expected national vote relying on available generic Congressional polls and the […]

The post What’s gonna happen in the 2018 midterm elections? appeared first on Statistical Modeling, Causal Inference, and Social Science.

What’s gonna happen in the 2018 midterm elections?

Following up on yesterday’s post on party balancing, here’s a new article from Joe Bafumi, Bob Erikson, and Chris Wlezien giving their predictions for November: We forecast party control of the US House of Representatives after the 2018 midterm election. First, we model the expected national vote relying on available generic Congressional polls and the […]

The post What’s gonna happen in the 2018 midterm elections? appeared first on Statistical Modeling, Causal Inference, and Social Science.