cultivating & crashing

an organic collection of notes, observations, and thoughts

Ultimate procrastination tip

In order to stop procrastinating, do nothing. If you’re putting off something, stop everything and sit in your miserable unease. I think this works because doing nothing at all is close to some strange form of torture that few can tolerate (see: meditation), and actually sitting down to work on what you’re supposed to be working on becomes preferable.

I want a god

I want a god
as my accomplice
a god
who hurts
to the last
bone and
bites the air
in pain
a jobless god
a striking god
a hungry god
a fugitive god
an exiled god
an enraged god
a god
who longs
from jail
for a change
in the order
of things
I want a
more godlike

Francisco X. Alarcón

Compassion hurts

Compassion hurts. When you feel connected to everything, you also feel responsible for everything. And you cannot turn away. Your destiny is bound with the destinies of others. You must either learn to carry the Universe or be crushed by it. You must grow strong enough to love the world, yet empty enough to sit down at the same table with its worst horrors.

Andrew Boyd

Null hypothesis testing: methodus non grato

The journal Basic and Applied Social Psychology just announced that it will no longer publish p-values, test statistics, confidence intervals, or any other null hypothesis testing procedures. This is pretty extreme, and equally exciting. From the little that I understand, Bayesian analysis is slowly but surely gaining ground against frequentist analysis, and this is one more (rather large) step in that direction.

Read the article here.

How old is epidemiology?

Seminar by Alfredo Morabia

1. 17th century move toward centralized states, organization of Europe after 30 year war

2. Crisis of Western ideas
Francis Bacon
– biases
– tabulating data
– determinants of longevity including heredity, height and weight, age, diet, behaviour, exercise, housing, medical treatment

– only trust “evidence”
– study one determinant at a time
– ignore interactions

Jan Baptista Van Helmont
– “Dawn or the New Rise of Medicine”
– iatrochemistry
– anti Galenist medicine: believed in diseases, separate from the individual, with external causes
– did not believe in blood letting (Van Helmont contest) “how many funerals each of us will have funerals” idea of fraction that will get better will be greater than your fraction that will get better was opposed to all mine will be cured and none of yours will

this is Renaissance thinking; will be implemented in the Enlightenment

3. Data!
Bills of Mortality (death certificates) in England

Bubonic plague – disruption of society and absolutist states
idea: plague has astrological cause or is transmitted by miasms

person would diagnose and count plague deaths, then publish them weekly
idea was to have a retreat outside of London when there was an outbreak
solution to the crisis every time there was an outbreak, based on weekly death counts, then add other causes of death, then births

4. Emergence of political arithmetic and capitalism
birth of epi is related to birth of capitalism

only merchants could deal with numbers, or intellectuals

William Petty “political arithmetic”

John Graunt: Natural and Politcal Observations made on Bills of Mortality (1662)

births and deaths = gains and losses. the same skills for tracking small margins of business was applied to deaths.

5. Royal Society of London (1661)
– centralized intellectual activity and skills
– “Nvllivs in Verba” no words or no speculation, only observation

Graunt is the convergence of these things
“The Table of Casualties” shows there is regularity of health phenomena
Was able to say that plague came from outside London, which was not the same for stable diseases
as a result, more quarantine enforced, and the plague stops affecting London

The Table of Casualties

Huygen’s adaptation of Graunt’s lifetable – median survival age
why asked this? how much should ask from people buying life insurance!

So how old is epidemiology? 1662 Graunt’s observation, our Big Bang. So 353 years in 2015!


Marz. read the book, asks how to educate everyone in the world, as Morabia says we should. Need to promote “epidemiological literacy”. No one understands epi spontaneously; it requires learning to understand interpretation. That’s why epi should be taught in high school, and become part of general culture.
asks 16 year olds : what do you know about health?
marijuana does x. Can get STIs. HOW DO YOU KNOW?
Ah! That’s the question.

Things epidemiology taught me

Everything is about confounding.
Never leave home without a calculator.
Odds ratios are backwards and non-intuitive and misunderstood, but quite clever if used properly.

In other news, I plan on spending some time reading about the natural logarithm because I want to truly understand what the hell is going on in logistic regression, and how it can give risks/probabilities even when the odds ratio doesn’t approximate the risk ratio (?!).

In other other news, after months of research and asking around, I finally bought a little Opinel to fill the void left by the Victorinox of my childhood. Unassuming and efficient, it’s hard not to fall in love.

R Notebook

IPython, but for R. I cannot wait to use this on my next data analysis assignment!

When statistical significance is statistically insignificant

This is my new favourite thing.

By the authors of Bayesian Data Analysis, a paper published in The American Statistician entitled “The Difference Between “Significant” and “Not Significant” is not Itself Statistically Significant.”

How to install and run WinBUGS on Mac OS X

A guide for non-geeks

  1. Download Wineskin Winery
    Direct link:
    a. Click “Wineskin Winery … (click me to download)”
    b. Click “Save File” to accept the Wineskin Winery app
    c. Find the .zip file in your Downloads folder and click on it to expand (unzip) it
    d. The Winery app should now appear (red icon)
    e. Click on the Winery app to open it
  2. Download the WinBUGS.exe file from the MRC website
    Direct link:
  3. Save the key
    a. Click the link for the key
    (Direct link:
    b. If the .txt file opens in the browser, save it (⌘S) to your Downloads folder
  4. Save the patch
    a. Click the link for the patch under the Quick start heading
    (Direct link:
    b. If the .txt file opens, save it, too
  5. Configure your Wineskin app
    a. Go to your opened Wineskin app, click on the + to install an engine
    b. Click “Download and Install” to get the most recent engine
    c. Click “OK” at the dialog box
    d. Click “Update” to update Wineskin, and “OK” at the dialog box
    e. Click “Create New Blank Wrapper” to do exactly that
    f. Type in WinBUGS to name your new wrapper
    g. Allow Wineskin to accept incoming network connections
    h. Click “Install” at the Wine Mono Installer
    i. Click to view wrapper in Finder
    j. Drag your WinBUGS wrapper to your Applications folder
    k. Click on the WinBUGS wrapper to open in
  6. Install WinBUGS in Wineskin
    a. Click on “Install Software”
    b. Click “Choose Setup Executable”
    c. Select the WinBUGS14.exe file from your Downloads folder
    d. The WinBUGS installation wizard will now open; click “Next>” until installation is complete, then click “Finish”
    e. Wineskin will ask you which executable file to use, select WinBUGS14.exe and click “OK”
  7. Run WinBUGS
    a. Click on your WinBUGS wrapper in your Applications folder to open WinBUGS
    8. To add the key and patch to WinBUGS, follow the directions in each .txt file

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.


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