# Category Archives: Statistics

## A Good Way to Estimate the Effects of COVID-19 Vaccination

Recently, there have been a slew of TV reports, tweets, and the like with statistics like “[some really high percentage] of hospitalized patients are unvaccinated” which are arguing that vaccination is a very good thing. To preempt any antiva assholesâ€“seriously, … Continue reading

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## COVID-19, Gyms, and Oslo: The Power of Rarity

I’m sort of surprised this NYT article describing an unreviewed manuscript about gym use and COVID-19 spread in Oslo, Norway hasn’t gotten more play. Here’s a synopsis (boldface mine): Like many countries, Norway ordered all gyms to close in March … Continue reading

Posted in COVID-19, Statistics | 6 Comments

## D.C.’s COVID-19 Data Problems

I wrote this before yesterday evening’s phone conference with reporters (obviously, I wasn’t on it). DC Health sort of suspended the march to fourteen days and moved it back to eleven days, since they claim, based on this figure, that … Continue reading

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## Science Reporting, Serology, and Bayes Theorem

Last week, we discussed the implications of Bayes Theorem on estimating the actual prevalence. Specifically (foreshadowing with a bad pun here), the specificity of a test measures the probability that someone who tests seropositive wh is not seropositive is really … Continue reading

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## Bayes Theorem, COVID-19, and False Positives

During the last week, there has been an upswing in discussions of Bayes Theorem regarding serotype testing for COVID-19. We’ll get to Bayes in a bit, but first, serological testing. Serological testing has the potential to identify who has been … Continue reading

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## Biologists Should Not Learn How to Code

Update added here OK, that’s a little extreme, but over the Thanksgiving weekend, I came across some advice which essentially amounted to biologists should learn how to code. I’m not sure that’s great advice. Since I’m in the genomics bidness, … Continue reading

Posted in Bioinformatics, Computers, Statistics | 5 Comments

## Understanding the Limitations of Your Data: The Student Debt Edition

As I’ve noted many times, when doing analysis, you must understand the limitations of your data, whether it be the microbiome, genomics, education statistics, polling data, or, well, anything else. With presidential candidates Sen. Elizabeth Warren and Bernie Sanders both … Continue reading

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## How to Use Polling Data for Gaslighting Clickbait

Consider this part of our ongoing series in how not to use polling data. This head-explodey tweet came across the transom recently: For the third week in a row, The Economist/YouGov polling shows that the share of Democratic primary voters … Continue reading

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## Revisiting Misadventures in Interpreting Democratic Primary Polling Data (LIZLADS ARE THE WORST)

Since we’re discussing the Democratic primaries, I’ll began with my typical disclosure that, were I voting today, I would vote Warren. A month ago, Emerson Polling released a poll, which led to wailing and gnashing of teeth in certain quarters: … Continue reading

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## When Standard ‘Pundit Talks To Pals’ Behavior Is Gussied Up With Numbers

Et tu, 538? One of the long-standing problems in political punditry is when pundits consider the group of people they know, a group which is almost always completely unrepresentative of the phenomenon they’re discussed, as a representative sample. Seth Masket, … Continue reading

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