Links

(i) Vaccines work; and here are the facts in comic form (medium.com)

(ii) On a related note, Steve Novella discusses the evolution of pertussis (whooping cough) bacteria:

One can already argue that it is everyone’s duty to get vaccinated, not only to protect themselves but to contribute to herd immunity for everyone. We can now reasonably argue that this duty extends to minimizing resistance to the existing vaccines. Non-compliance can not only lead to outbreaks, but to diminishing effectiveness of the vaccines for everyone.

(iii) Yet another example Goodhart's law, "When a measure becomes a target, it ceases to be a good measure." Did Northeastern University game college rankings? Or did it just excel at something that every university tries to do?

(iv) NPR's story about fear-mongering by the Food Babe elicited a response at her site. David Gorski at science-based medicine offers a useful summary in his response to her response.

(v) While on the matter of food, here's Scott Adams on how you may want to think about atoning for the "eating season" we are currently in.

Python for Matlab Users

As part of our MCMC seminar series this semester, we've adopted Python as the language that we will all write code in. While I've spent plenty of time programming in Octave and Matlab, I have only dabbled with Python here and there.

This time, I thought I'd make a concerted effort to get past that initial hump.

You know, you got to roll a snowball to a certain size, before it launches an avalanche.

Here are resources that I found useful:

1. Introduction to Python and Problem Solving with Python (pdf) by Sophia Coban (H/T Walking Randomly). The first presentation introduces you to Python in general, the second talks more about modules. More importantly it also compares array and matrix operations in Matlab and numpy.
2. Another simple introduction (pdf) to numpy and scipy by M. Scott Shell at UCSB.
3. If you don't want a PDF link, here is a tentative numpy tutorial in HTML.

Tyco Brahe: Who says Scientists are Boring?

An entertaining portrait of "history's strangest astronomer".

Still, his life seems almost dry and tedious compared to his mysterious death. He died of a sudden bladder disease in 1601 while at a banquet in Prague. He was unable to urinate except in the smallest of quantities, and after eleven days of excruciating agony he finally died. At least, that's the official story. It's possible he actually succumbed to mercury poisoning, as later researchers have detected toxic quantities of the substance on his mustache hairs. 

In order to shed some more light on this, his remains were recently exhumed for further medical study. Assuming the researchers find more evidence of mercury on his bone and hair samples, there are two possibilities. If there's evidence of longer-term exposure, then he likely ingested the mercury accidentally during the course of his experiments. If, on the other hand, the mercury can only be found right at the roots of his hair, then that would indicate he was given one big fatal dose of mercury. And that means...murder!

I am not sure how much to drama has been added in the article, though. I thought Tyco Brahe died a bizarre, but less malicious, death as echoed in the wikipedia entry:

Tycho suddenly contracted a bladder or kidney ailment after attending a banquet in Prague, and died eleven days later, on 24 October 1601. According to Kepler's first hand account, Tycho had refused to leave the banquet to relieve himself because it would have been a breach of etiquette.

The same entry entertains, but quickly dismisses, the mercury poisoning story, by suggesting that the mercury could have come from the metal noses he wore.

Further down,

In life, Brahe had jealously guarded his data, not even letting his prized pupil Johannes Kepler gain access.

That all changed upon his death, as Kepler took advantage of the confusion to take possession of the data, something he himself later admitted was not entirely ethical:

"I confess that when Tycho died, I quickly took advantage of the absence, or lack of circumspection, of the heirs, by taking the observations under my care, or perhaps usurping them." 

With that data in hand, Kepler was able to move astronomy further forward than anyone before him, becoming what Carl Sagan would later call "the first astrophysicist and the last scientific astrologer."

What the Deal with Oil?

A fascinating animated infographic on how the domestic demand for oil (as a percentage of GDP) has fallen, even as production has increased, the average car has become more fuel efficient, and the shift to renewables has begun in earnest.

Check it out at Bloomberg. 

Links

1. Formula versus Breast Feeding

The Reality Check explores this unnecessarily controversial topic. The show notes are extensive, and worth a look. The bottomline is that difference between breast milk and formula is usually overstated by its proponents, and exacts a heavy emotional toll from mothers who have trouble breast-feeding

2. Sandy, Issac and the Red Cross

ProPublica and NPR presents a damning expose'.

3. Scilab and Textbook Companion Project (H/T Michael Croucher)

Prof. Kannan Moudgalya, a former teacher or mine at IIT Bombay, and his team ported code from a gazillion engineering textbooks to Scilab. Impressive feat of endurance!

Newcomb's paradox

I learnt about Newcomb's paradox recently. Wikipedia has a nice post on it.

The player of the game is presented with two boxes, one transparent (labeled A) and the other opaque (labeled B). The player is permitted to take the contents of both boxes, or just the opaque box B. Box A contains a visible $1,000. The contents of box B, however, are determined as follows: At some point before the start of the game, the Predictor makes a prediction as to whether the player of the game will take just box B, or both boxes. If the Predictor predicts that both boxes will be taken, then box B will contain nothing. If the Predictor predicts that only box B will be taken, then box B will contain $1,000,000.

The Predictor is almost infallible.

The range of possibilities are (from Wikipedia):

1. One can say that "A and B" is a superior choice, because given a predicted choice (which one can't control) it offers a better payout.

If the Predictor was not very reliable, then this would certainly be the better choice.

2. One can say that "B only" is a better choice, because the Predictor is almost always right. Thus, the probability of a mismatch between predicted and actual choices is so small that we might ignore it. Therefore, one should look at only the first and last rows in the table above, and "B only" offers a higher payout.

If the Predictor very perfectly reliable, then this would certainly be the better choice.

There is a lot of commentary and nuance to this topic, so go google it.