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Random Numbers

This category contains 11 posts

Measurement appreciation day

Measurement appreciation day In the 2 July 2017 issue of Nature, there is an article in the Comment section about the science of measuring: http://www.nature.com/news/metrology-is-key-to-reproducing-results-1.22348 The moral of the article is that if we all actually measured properly it would go a long way towards fixing our reproducibility problem. Good point, that unfortunately has to [...]

Standard Error isn’t, so don’t burden your audience with it

I am aware that there are entire fields as well as high impact journals that overlook this mistake, but I want to bring up, (yes, again), why you should always use the standard deviation when drawing error bars or reporting the uncertainty about the data you actually collected; that is, why you should not report [...]

Teach about confirmation bias. Please.

I am on a mission to spread the news of this transformational (yes!) exercise for all teachers of all subjects, but especially scientists. It is called the Wason* 2-4-6 Task, (I’ve seen it referred to as the 2-4-8 test). It is the best exercise I’ve ever seen for demonstrating the perils of confirmation bias.  It [...]


Hi Dany Spencer Adams, I think there might be an error in the equation for converting RCF to rpm on page 140 of the second edition, hardcover. Should the equation be: rpm= (RCF / (r x 1.118 x 10^-6))^1/2 instead of 10^-5? because the radius is measured in mm? … E. D. Dear E. D. [...]

The Patriots, the Nobel Laureate, and the power of uncertainty

Chemistry Nobel Laureate Roderick MacKinnon has done a wonderful (by which I mean numerically sound) analysis of the analysis of the Patriots’ footballs.  This is yet another example of the cost of not understanding uncertainty:  was it $2 million?  If Brady would like me to teach him, I’ll take a mere half of that. Analysis of [...]

It’s just multiplication, have no fear

(A true story, with some added sarcasm, to illustrate that using equations is safer in the long run than trying to avoid using equations)   My lab has a new centrifuge that I recently needed to use for the first time.  Like most centrifuges, you can set the rotations per minute (RPM) and the number [...]

Graphing Advice

How to Make Truly Terrible Graphs: A Tutorial by David Streiner Part 4: Where’s the Y?   In previous blogs, I described how to make terrible graphs using some of the features of leading graphing packages, such as pie charts and 3-D graphs. But, this is unfair to users of other programs that do not [...]

Graphing advice

How to Make Truly Terrible Graphs: A Tutorial David L. Streiner, special guest contributor and co-author of excellent statistics texts Part 3 – 3D or not 3D In the two last blogs, we learned the first steps in making truly terrible graphs: by confusing the role of a visual with that of a table, and by [...]

Fabulous correlations

Who would have thought that you can predict the number of drivers killed in collisions by monitoring US crude oil imports from Norway.  Actually, shockingly, this one of those correlation vs causation things.  Check out the excellent collection kept by Tyler Vigen at: Spurious correlations   (thanks to Dr. David Streiner for alerting us to [...]

Statisticians 10? Where are you getting your statistics?

A recent article, curiously enough in the Styles section of the New York Times, had the title: Statisticians 10, Poets 0. The article was about the growing number of numbers reported to “us” (an undefined population, but apparently we all use apps and watch cable TV). Poets 0 refers to the paucity of poetry. With [...]

Birth of the Blog

This blog, like the book Lab Math from which it springs (incompletely formed), will be about numbers. I will endeavor to:

1. showcase the basic and the practical, not the challenging or even the advanced;

2.. provide straightforward guidance for the unenthusiastic (“just do it exactly this way”);

3.. provide refreshers for those needing refreshment (whether they know it or not.)