forget Obamacare and SCOTUS: it’s Tau day! it’s Back to the Future Day!

So, apparently there was this big hoo-hah today about some political thing or the other. But the real significance of today is this:

Back to the Future.. but the Future is NOW!

That’s right – today is the day that Doc set as the Future in the first Back to the Future movie!

UPDATE: No, it wasn’t. Three years too early. Sigh.

What’s more, today is also June 28, or “6/28” – which means it is Tau Day! What is tau, you ask? It’s the true circle constant (6.28), unlike that upstart Pi. For more details on the primacy of Tau and the centuries-old conspiracy that is Pi, see the Tau Manifesto, though really I think this image says it all:

Tau is one turn

and here’s a snappy little music video too:

so, enjoy today, a most historic and important day! And don’t worry/gloat too much about that other thing. It’s really not as important as this.

Martin Gardner, 1914 – 2010

A legend has passed away last week: Martin Gardner, arguably the inventor of the term “recreational mathematics” and columnist for Scientific American for almost 30 years.

Here are tributes to Gardner at Discover Magazine, Scientific American, and also some thoughts by Richard Dawkins. I find it interesting that Gardner is remembered for his skepticism; I wonder how many people praising him for it are also true believers in the Singularity? (a concept ever deserving of Gardner’s critique, if there ever was one. My skepticism on Singularity is a matter of record).

Pi Day is March 14th (3/14)

I am geeked out by this – finally, formal recognition for the number pi!

An irrational number that has been calculated to more than 1 trillion digits, pi is a concept not totally foreign to today’s Washington. But in this case, the goal was to promote efforts by the National Science Foundation to improve math education in the United States, especially in the critical fourth to eighth grades.

Rounded off, pi equates to 3.14, hence the designation of March 14 as Pi Day under the resolution. Informal celebrations have been held around the country for at least 20 years, but Thursday’s 391-10 vote is the first time Congress has joined the party.

So who exactly were the ten who voted against? What are they, non-Euclideans or something?

Incidentally, one of my close friends from grad school is actually getting married today. Congratulations, Dustin and Gwen!

election math

I just finished extolling the virtues of keeping politics out of the Otakusphere, but this isn’t really a post about politics, it’s about math. Besides, only a geetaku audience can appreciate this.

Good Math Bad Math points out the innumeracy of many election-beat reporters who seem to be unaware of how percentages work:

as results were coming in from Ohio, one reporter was saying “Black turnout in Cleveland was only around 18%, which is only up 2% from four years ago”. That’s a rather classic bad-math error. A two percent increase over 16% is 16.32% – which is a trivial change. A change from 16% to 18% is actually a 12.5% increase – which is very significant.

At the opposite side of the scale, I think it’s astounding just how eerily accurate Nate Silver of fivethirtyeight.com was regarding his predictions. The cool thing about his methodology is that he actually simulates the election results in Monte Carlo fashion, running each one 10,000 times:

The basic process for computing our Presidential projections consists of six steps:

1. Polling Average: Aggregate polling data, and weight it according to our reliability scores.

2. Trend Adjustment: Adjust the polling data for current trends.

3. Regression: Analyze demographic data in each state by means of regression analysis.

4. Snapshot: Combine the polling data with the regression analysis to produce an electoral snapshot. This is our estimate of what would happen if the election were held today.

5. Projection: Translate the snapshot into a projection of what will happen in November, by allocating out undecided voters and applying a discount to current polling leads based on historical trends.

6. Simulation: Simulate our results 10,000 times based on the results of the projection to account for the uncertainty in our estimates. The end result is a robust probabilistic assessment of what will happen in each state as well as in the nation as a whole.

This is a more stochastic approach to election prediction which I think matches reality very well.

I also found this collection of links, which are dangerously interesting. Among them, “The Mathematics of Voting“:

Mathematical economist Kenneth Arrow proved (in 1952) that there is no consistent method of making a fair choice among three or more candidates. Topics cover Fairness Criteria, Voting Methods, Fairness Criteria applied to Voting Methods, and Ranking Procedures.

Then there’s the old favorite topics, like should we ditch the Electoral College? (no). Should we use an Instant Runoff Voting system instead? (no).

Election math is cool.