“Oxford mathematician Peter Donnelly reveals the common mistakes humans make in interpreting statistics — and the devastating impact these errors can have on the outcome of criminal trials.”
“A shocking amount of what we’re reading is created not by humans, but by computer algorithms. Can you tell the difference? Take the quiz.”
http://www.nytimes.com/interactive/2015/03/08/opinion/sunday/algorithm-human-quiz.html
“Because, these days, a shocking amount of what we’re reading is created not by humans, but by computer algorithms. We probably should have suspected that the information assaulting us 24/7 couldn’t all have been created by people bent over their laptops.”
“With technology, the next evolutionary step always seems logical. That’s the danger. As it seduces us again and again, we relinquish a little part of ourselves. We rarely step back to reflect on whether, ultimately, we’re giving up more than we’re getting.”
“Over at the Washington Post, Brad Plumer looks into the question of whether a wealthy person could guarantee himself a win by buying every possible ticket in the Mega Millions lottery, and discovers that the answer is no:”
http://www.forbes.com/sites/joshbarro/2012/03/30/can-you-ever-guarantee-a-mega-millions-win/
Much of our charitable giving is governed by emotions. We are far more often to give to a cause if the story or cause grabs our attention by moving us emotionally. Sometimes the charities are effective at branding themselves or their cause and sometimes we personally identify with the cause.
There are some people who want to change the way we think about charitable giving by identifying the “return on investment” of each dollar donated rather than letting our emotions decide for us. What happens when we decide to figure out the most effective use of our charitable dollars? How can we measure the impact? What criteria do we look at? Do we focus on saving lives or improving quality of life? Is it possible to even quantify these things?
Much of the approach these people use try to apply mathematical approaches to identify effectiveness. How can we use math to help us determine truth? What are the assumptions built into these mathematical models? Does quantifying this stuff to determine effectiveness dehumanize charitable work?
What if it was “mathematically proven” that the the most effective approach to charity were to give money away with no conditions or strings attached to the recipients? Would your emotional or intuitive revulsion to such an idea keep you from donating? How do you decide what is right when different ways of knowing conflict with one another?
Sometimes people prefer to donate to causes that build tangible structures like schools in foreign countries though it turns out that building schools may not actually that effective based on the cost.
Below are some links to evaluate this topic and these questions.
1. Is It Nuts to Give to the Poor Without Strings Attached?
2. Planet Money Podcast: The Charity That Just Gives People Money
3.Measuring the Bang of Every Donated Buck
Scoring charitable work is evolving from an art into a science
http://www.wsj.com/articles/SB10001424052748703787304575075340954767332
4. Give Well: Real Change for Your Dollar
Homepage for an organization that seeks to quantify the impact of various charities.
http://www.givewell.org/international/technical/criteria/cost-effectiveness
5. Smart Aid for the World’s Poor
How can rich countries best help poor ones? Matt Ridley identifies five priorities
http://www.wsj.com/articles/smart-aid-for-the-worlds-poor-1406326677
6. Freakonomics Podcast:Fixing the World, Bang-for-the-Buck Edition
7.Don’t Build Schools in Afghanistan
http://www.slate.com/articles/business/moneybox/2011/05/dont_build_schools_in_afghanistan.html
8.Poker Players Use Science To Effectively Give To Charities
http://www.npr.org/2014/12/24/372837159/poker-players-use-science-to-effectively-give-to-charities
The old game show, Let’s Make a Deal, featured a segment in which contestants could choose the prize behind one of three doors. “Behind one door is a car; behind the others, goats. You pick a door, say No. 1, and the host, who knows what’s behind the other doors, opens another door, say No. 3, which has a goat. He then says to you, ‘Do you want to pick door No. 2?’ Is it to your advantage to take the switch?”
This case provided an interesting case of conflict between our intuitive beliefs and math. This problem was so simple yet confusing, even math professors and other experts got it wrong. Below is an article about the whole story and below that is a link to play an online version of the game in which you can choose a door and then decide whether to switch. The site tallies your overall effectiveness at winning the prize.
http://www.nytimes.com/1991/07/21/us/behind-monty-hall-s-doors-puzzle-debate-and-answer.html
How do we use mathematics to make predictions about the future? Upon what assumptions do we build mathematical models? Why do these techniques sometimes come up short?
“The models relied on old and partial figures. These were plugged into equations whose key variable was the rate at which each case gave rise to others. But this “reproduction number” changed as outside help arrived and those at risk went out less, avoided physical contact and took precautions around the sick and dead. So difficult are such factors to predict that epidemiologists modelling a disease often assume that they do not change at all.”
“Mathematics, rightly viewed, possesses not only truth, but supreme beauty a beauty cold and austere, like that of sculpture, without appeal to any part of our weaker nature, without the gorgeous trappings of painting or music, yet sublimely pure, and capable of a stern perfection such as only the greatest art can show. The true spirit of delight, the exaltation, the sense of being more than Man, which is the touchstone of the highest excellence, is to be found in mathematics as surely as in poetry.”
–BERTRAND RUSSELL, Study of Mathematics
https://www.dartmouth.edu/~matc/MathDrama/reading/Wigner.html
“You’ve never seen data presented like this. With the drama and urgency of a sportscaster, statistics guru Hans Rosling debunks myths about the so-called ‘developing world.'”
“Now a team of Italian researchers has found that newborn chicks, like humans, appear to map numbers spatially, associating smaller amounts with the left side and larger amounts with the right side.”
http://www.nytimes.com/2015/01/30/science/left-means-less-even-for-chickens.html?_r=0
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