cultivating & crashing

an organic collection of notes, observations, and thoughts

Tag: science


L’intelligence ce n’est pas ce que l’on sait, mais ce que l’on fait quand on ne sait pas.

Jean Piaget


Lest our measurements of intelligence be confounded by knowledge!

I find this really interesting, because he is not stating what he would consider intelligent to do. Strict epi would have you say you don’t know and back away from the problem, but we need to make decisions all the time for problems on which we don’t have data. So does that mean prudence or daring?


Vintage data viz porn

“The commonality between science and art is in trying to see profoundly – to develop strategies of seeing and showing.”

Edward Tufte


I’ve just spent a a stupid amount of time admiring this collection of slopegraphs. Who thought train schedules could be mesmerizing?


Finally, some beauty for this Friday afternoon:



Napolean’s Russian campaign by Minard


Notes from Bad Science

Make kedgeree

Read about this intervention


noun, Computer Slang.
a software or hardware configuration that, while inelegant, inefficient, clumsy, or patched together, succeeds in solving a specific problem or performing a particular task.

Nullis in verba — On the word of no one
Royal Society’s motto

Statistical armageddon / scientific postmodernism

Idea: As our scientific precision increases, it is necessary to proportionally (or exponentially) expand our capacities for computing the effect. Example: in order to definitively statistically detect a difference in males and females in incidence of heart attacks we might need, say, a total sample size of 100 (so that we have 50 people in each group so that our statistical calculations will be robust enough to make solid conclusions from). But as we learn more about heart attacks, we realize that there are more variables that affect heart attacks, like age, diet, physical activity, abdominal adiposity, educational attainment, socio-economic status, smoking, and alcohol consumption. Assuming each of these variables are dichotomized into only two groups (young, old; healthy diet, unhealthy diet; active, inactive; etc.) and that 50 people in each group is still enough to detect true difference in each variable (which is unrealistic), we would now need 25,600 people to tease out the effects of all of these different variables. With more nuanced categories, this number climbs very quickly. We know a lot about heart attacks nowadays but there is still unexplained variation in the effects we see, which means there are other things we’re not measuring and accounting for.

Not think of whole-genome research, where we are handling approximately no less than 125 megabytes of information from just one single person. Now think of the entire genome of one person’s entire microbiome. How many people would we need then? More than exist on Earth.

My prediction is that soon we’ll realize that the more we know, the less we can continue to learn. We will be reduced to underpowered tests of small questions. We will have hit an upper limit of what we can isolate or definitively know about anything, and there will be nothing we can do about it. (But before that, our computers will not have enough computing power and even before that we will never have enough money to even begin to do one sound study of these proportions). We’ll get to the point where we must resign ourselves to not knowing what we want to know. Science will become postmodern, accepting that we can’t do what our methods set out to do. It will be a kind of scientific Armageddon, having arrived at the limits of statistical possibility.

Just a thought.

In the meantime I’m now wondering if I can use Bayesian data analysis to analyze prevalence of diabetes to account for error in diagnosis. “Live by the harmless untruths that make you brave and kind and healthy and happy.

Imperfect data

The art of epidemiologic reasoning is to draw sensible conclusions from imperfect data.”

George W. Comstock

American Journal of Epidemiology 1990

5 years

WordPress just informed me that I registered with them five years ago today. Woot! It’s been fun. Wonder how the story will continue. 

Here are two excellent articles from the NY Times, one lamenting how easily scientific fact is discredited nowadays, and the other about the need to update the racial categories used in the US Census.

7-minute workout

If the NYTimes is to be trusted, this was the best 10 minutes I will have spent today. Well played, exercise science.

Klika, B., & Jordan, C. (2013). High-Intensity Circuit Training Using Body Weight: Maximum Results with Minimal Investment. American College of Sports Medicine’s Health and Fitness Journal, 17(3), 8-13. doi: 10.1249/FIT.0b013e31828cb1e8

No science, no evidence, no truth, no democracy

First he annihilates the Census. Now he cuts funding for this amazing program dedicated to understanding what we’re doing to the place we depend on for survival (i.e., the earth). It’s clear: Harper hates science. I wonder to what extent this reflects the Canadian people.

No science, no evidence, no truth, no democracy, by Michael Harris

I wonder why such governments are popular. In gross generalizations, do prosperity and science really clash that much? Maybe the likes of Erich Fromm are right: a lot more about the world than I would like to think can be explained by psychological factors and limitations of humans. We’re selfish and narrow-minded, can only think short-term, or we’re in denial. We are not rational creatures. I guess it’s taking me a long time to truly understand this.

At any rate, I imagine this means in the future, science will have to learn to fight in politics. Scientists are smart, now they have to learn to be pragmatic. I don’t think this is a bad thing. I’m just scared of finding out that we’re collectively stupid enough to move away from scientific endeavours in a significant way when push comes to shove.