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In my quest to find more ways to procrastinate from dissertation-editing, I wound up skimming Harvard Business Review. In it there was an article entitled Do Women Take as Many Risks as Men?. It noted certain effects like, to quote a cited paper, that "stress amplifies gender differences in strategies used during risky decisions, as males take more risk and females take less risk under stress". What you also find is the following:

Risk-taking role models of both genders are important in an increasingly complex world. When facing a risky decision, leaders must weigh a lot of factors. Two of the biggest are, first, the likelihood that the risk in question will help hit strategic objectives and, second, the effect the risk will have on people involved. Accounting for one without the other is a recipe for disaster. In my consulting practice I've noticed a tendency for men to put a stronger emphasis on the former and women on the latter. Recent research by Seda Ertac and Mehmet Y. Gurdal supports this observation. To me, this tendency is further evidence that the most successful risk taking is a collaborative effort between men and women (and likely across other differences as well).

The article's author then argues that

... [t]he trouble is that historically risk-taking has been framed so narrowly that it skews our perceptions. For example, the majority of studies that point to men having a greater inclination for risk-taking define risk in physical and financial terms. They don't point to risks like standing up for what's right in the face of opposition, or taking the ethical path when there's pressure to stray — important risks that I've found women are particularly strong at taking. If these sorts of risks were fully accounted for in our business culture, would it balance the gender perception? I think it would.

It would seem somewhat unlikely to have businesses focus away from seeing risk in financial terms though.

Been reading Statistics Done Wrong and it pointed me to a paper that addressed the question that's the title of this post:

Conditional probabilities: The probability that a woman has breast cancer is 0.8%. If she has breast cancer the probability that a mammogram will show a positive result is 90%. If a woman does not have breast cancer the probability of a positive result is 7%. Take, for example, a woman who has a positive result. What is the probability that she actually has breast cancer?

... We see quickly that only seven of the 77 women who test positive actually have breast cancer, which is one in 11 (9%).

How good do the authors find doctors to be at interpreting such statistics?

When asked to estimate the probability that a woman with a positive screening mammogram actually has breast cancer, doctors who received conditional probabilities gave answers that ranged from 1% to 90%; very few of them gave the correct answer of about 8%.

The authors of Statistics Done Wrong have a little more to say on how well people interprete such data:

If you administer questions like this one to statistics students and scientific methodology instructors, more than a third fail.8 If you ask doctors, two thirds fail.

I seem to vaguely recall seeing such an example back once-upon-a-time when I took statistics. The answer of 9% might also tell you why medical officials are questioning the value of routine mammograms.

(Hmm... interesting. Realized that the paper separately notes figures of approximately 8% and 9%. Seems that if you look at the data in terms of natural frequencies you wind up with rounding giving you a slightly lower result here).

Worrying demographic changes

From a Chinese government portal: "China's working-age population, that is people aged from 15 to 59, registered a rare and worrying decline in 2012, decreasing by 3.45 million to 937 million, according to the National Bureau of Statistics. ... This is worrying as the NBS predicts the decline will continue to 2030." It's hard to describe something as "rare" when it's predicted to continue to 2030 (and, given the one-child policy, seems likely to continue further after that).

Israelis urged to be ‘vigilant’ after locusts descend on Egypt ahead of Passover

Locust count: over 30 million

Leg injury cuts short female kicker's NFL tryout

Just a quick reminder that most major sporting leagues typically don't prohibit women from playing.

Stalin’s Long Shadow

"In 1994, 27 percent of Russians had a positive view of Stalin. In 2011 it was 45 percent. Fifty percent of the respondents thought that Stalin was a wise leader who brought might and prosperity to the Soviet Union. Yet at the same time, 68 percent agreed that he was a cruel tyrant guilty of the death of millions of innocent citizens."

From ars technica:

What scientists actually do is think about what they don’t know. “The ignorance is what’s missing” from public discussions of science, Firestein told the crowd. As a word, “ignorance” is potentially provocative, so he clarified. Firestein means "ignorance" in the sense that science focuses on recognizing and studying communal gaps in knowledge (rather than lauding the village idiot). This is the exciting part of science: “the boundary just outside the facts.”

Basically the piece is arguing that one of the things that turns people off science is how science education often focuses on accumulating a large body of facts rather than exploration of the boundaries of knowledge.

Of course, you do need a certain base of knowledge to explore some areas further, but if you could build that base up in a more-exploratory fashion perhaps that might help.