Author Archives: Tim Erickson

About Tim Erickson

Math-science ed freelancer and sometime math teacher. In 2014–15, at Mills College in Oakland, California.

Reflection on 538, Trump, and Bayes

Was the run-up to the recent election an example of failed statistics? Pundits have been saying how bad the polling was. Sure, there might have been some things pollsters could have done better, but consider: FiveThirtyEight, on the morning of the election, … Continue reading

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Modeling Hexnut Mass

Let me encourage you to go to your hardware store and get some hexnuts. You won’t regret it. Now let’s see if I can write a post about it in under, like, four hours. (Also, get a micrometer on eBay … Continue reading

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DASL Updated. Mostly improved.

The Data and Story Library, originally hosted at Carnegie-Mellon, was a great resource for data for many years. But it was unsupported, and was getting a bit long in the tooth. The good people at Data Desk have refurbished it … Continue reading

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Model Shop! One volume done!

Hooray, I have finally finished what used to be called EGADs and is now the first volume of The Model Shop. Calling it the first volume is, of course, a treacherous decision. So. This is a book of 42 activities … Continue reading

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The Index of Clumpiness, Part Four: One-dimensional with bins

In the last three posts we’ve discussed clumpiness. Last time we studied people walking down a concourse at the big Houston airport, IAH, and found that they were clumped. We used the gaps in time between these people as our … Continue reading

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The Index of Clumpiness, Part Three: One Dimension

In the last two posts, we talked about clumpiness in two-dimensional “star fields.” In the first, we discussed the problem in general and used a measure of clumpiness created by taking the mean of the distances from the stars to … Continue reading

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The Index of Clumpiness, Part Two

Last time, we discussed random and not-so-random star fields, and saw how we could use the mean of the minimum distances between stars as a measure of clumpiness. The smaller the mean minimum distance, the more clumpy. What other measures … Continue reading

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The Index of Clumpiness, Part One

There really is such a thing. Some background: The illustration shows a random collection of 1000 dots. Each coordinate (x and y) is a (pseudo-)random number in the range [0, 1) — multiplied by 300 to get a reasonable number … Continue reading

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Capture/Recapture Part Two

Trying to get yesterday’s post out quickly, I touched only lightly on how to set up the various simulations. So consider them exercises for the intermediate-level simulation maker. I find it interesting how, right after a semester of teaching this stuff, … Continue reading

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Capture/Recapture Part One

If you’ve been awake and paying attention to stats education, you must have come across capture/recapture and associated classroom activities. The idea is that you catch 20 fish in a lake and tag them. The next day, you catch 25 … Continue reading

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