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Archive of posts filed under the Statistical graphics category.

All maps of parameter estimates are (still) misleading

I was looking at this map of coronavirus cases, pondering on the large swaths with seemingly no cases. I moused over a few of the gray areas. The shading is not based on counties, as I assumed, but on some other spatial unit, perhaps zip codes or census blocks or something. (I’m sure the answer […]

Sleep injury spineplot

Antony Unwin sends along the above graph in response to this recent post. The data are kinda crap, but I agree with Antony that this plot is a good way of showing the number of cases corresponding to each histogram bar.

Misrepresenting data from a published source . . . it happens all the time!

Following up on yesterday’s post on an example of misrepresentation of data from a graph, I wanted to share a much more extreme example that I wrote about awhile ago, about some data misrepresentation in an old statistics textbook: About fifteen years ago, when preparing to teach an introductory statistics class, I recalled an enthusiastic […]

Alexey Guzey plays Stat Detective: How many observations are in each bar of this graph?

How many data points are in each bar of the top graph above? (See here for background.) It’s from this article: Milewski MD, Skaggs DL, Bishop GA, Pace JL, Ibrahim DA, Wren TA, Barzdukas A. Chronic lack of sleep is associated with increased sports injuries in adolescent athletes. Journal of Pediatric Orthopaedics. 2014 Mar 1;34(2):129-33. […]

Information, incentives, and goals in election forecasts

Jessica Hullman, Christopher Wlezien, and Elliott Morris and I write: Presidential elections can be forecast using information from political and economic conditions, polls, and a statistical model of changes in public opinion over time. However, these “knowns” about how to make a good presidential election forecast come with many unknowns due to the challenges of […]

“Pictures represent facts, stories represent acts, and models represent concepts.”

I really like the above quote from noted aphorist Thomas Basbøll. He expands: Simplifying somewhat, pictures represent facts, stories represent acts, and models represent concepts. . . . Pictures are simplified representations of facts and to use this to draw a hard and fast line between pictures and stories and models is itself a simplified […]

An example of a parallel dot plot: a great way to display many properties of a list of items

I often see articles that are full of long tables of numbers and it’s hard to see what’s going on, so then I’ll suggest parallel dot plots. But people don’t always know what I’m talking about, so here I’m sharing an example. Next time when I suggest a parallel dot plot, I can point people […]

Know your data, recode missing data codes

We had a class assignment where students had to graph some data of interest. A pair of students made the above graph, as a reminder that some data cleaning is often necessary. The students came up with the excellent title as well!

Coding and drawing

Some people like coding and they like drawing too. What do they have in common? I like to code—I don’t looove it, but I like it ok and I do it a lot—but I find drawing to be very difficult. I can keep tinkering with my code to get it to look like whatever I […]

The history of low-hanging intellectual fruit

Alex Tabarrok asks, why was the game Dungeons and Dragons, or something like it, not invented in ancient Rome? He argues that the ancient Romans had the technology (that would be dice, I guess) so why didn’t someone thing of inventing a random-number-driven role-playing game? I don’t have an answer, but I think we can […]

Roll Over Mercator: Awesome map shows the unreasonable effectiveness of mixture models

I’m not gonna link to all the great xkcd drawings cos if I did, I’d just be linking to xkcd every day, but today’s is just too good to pass by: He could’ve thrown in some Pacific islands and Scandinavia too, but it’s amazing in any case. The relevant statistical point here is how good […]

New report on coronavirus trends: “the epidemic is not under control in much of the US . . . factors modulating transmission such as rapid testing, contact tracing and behavioural precautions are crucial to offset the rise of transmission associated with loosening of social distancing . . .”

Juliette Unwin et al. write: We model the epidemics in the US at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the time-varying reproduction number (the average number of secondary infections caused by an infected person), the number of individuals that have been infected and […]

Hey, I think something’s wrong with this graph! Free copy of Regression and Other Stories to the first commenter who comes up with a plausible innocent explanation of this one.

Paul Alper points us to this column by Dana Milbank discussing the above graph from Georgia’s Department of Public Health: Ok, the comb-style bar graph is, as always, a bad idea, as it multiplexes two dimensions (county and time) on a single x-axis. The graph should be a lineplot, with one line per county, and […]

“Stay-at-home” behavior: A pretty graph but I have some questions

Or, should I say, a pretty graph and so have some questions. It’s a positive property of a graph that it makes you want to see more. Clare Malone and Kyle Bourassa write: Cuebiq, a private data company, assessed the movement of people via GPS-enabled mobile devices across the U.S. If you look at movement […]

Uncertainty and variation as distinct concepts

Jake Hofman, Dan Goldstein, and Jessica Hullman write: Scientists presenting experimental results often choose to display either inferential uncertainty (e.g., uncertainty in the estimate of a population mean) or outcome uncertainty (e.g., variation of outcomes around that mean). How does this choice impact readers’ beliefs about the size of treatment effects? We investigate this question […]

Make Andrew happy with one simple ggplot trick

By default, ggplot expands the space above and below the x-axis (and to the left and right of the y-axis). Andrew has made it pretty clear that he thinks the x axis should be drawn at y = 0. To remove the extra space around the axes when you have continuous (not discrete or log […]

We need better default plots for regression.

Robin Lee writes: To check for linearity and homoscedasticity, we are taught to plot residuals against y fitted value in many statistics classes. However, plotting residuals against y fitted value has always been a confusing practice that I know that I should use but can’t quite explain why. It is not until this week I […]

Tracking R of COVID-19 & assessing public interventions; also some general thoughts on science

Simas Kucinskas writes:

10 on corona

Here are some things people have sent me lately. They are in no particular order, except that I put the last item last so we could end with some humor. After this, I’ll write a few more blog posts, then it’ll be time to do some real work. Table of contents 1. Suspicious coronavirus numbers […]

Number of deaths or number of deaths per capita

Pablo Haya writes: Currently, there is a lot of data analysis in the news media showing multiple aspects of the COVID-19 crisis. Many of them compare the virus spread and evolution between different countries, or between different regions within each country. They use to compare the absolute frequency of several metrics such as confirmed cases […]