Show Me a Power Broker

Review of Power Broker and Show Me A Hero

This summer I read an all time great book, The Power Broker: Robert Moses and the Fall of New York. Writing about this book was one of the first blog posts I envisioned when designing this blog. It was also a major upset when Power Broker did not top my list of books in 2015, but I suspect it will only rise in esteem over time. In my mind, I have also begun linking it with arguably my favorite piece of media that debuted in 2015: the HBO mini-series, Show Me A Hero. 

The Power Broker is a biography of Robert Moses, a historical figure I had previously never heard of, but now constantly see references to. Moses, the chief urban planner in New York City serving in various roles from 1920's to the 1960's, was a cross between Leslie Knope and J. Edgar Hoover. He began as a progressive reformer, writing legislation in New York State as an aide to Governor Al Smith. As part of his reformist agenda, he championed the creation of park space. This eventually transitioned him into the head of Long Island Park Commission, where he designed a masterpiece recreational development.

Balls Out

An analysis of  the frequency with which customers choose Powerball numbers

I told you that I got a little obsessed with the Powerball lotto last week, when I broke down the behavioral economics behind my decision to join an office pool. Well the obsession continued, as I searched for an optimal strategy for playing the lottery. Plus, writing about the Powerball again allows me pull out more "ball"-related double entendres.

Optimal strategy, isn't it a lottery? That's a reasonable question, as the whole lottery just comes down to picking some random numbers. But, when the lotto gets as popular as this last one did, someone who buys the ticket is not just playing against a random number generator. They are also playing against everyone else who bought a ticket. This is, of course, because as more tickets are bought, the probability that many players purchase a winning ticket increases. If this happens, the winners split jackpot and each buyers' share is smaller.

Power Ballin'

Behavioral Economics and the Largest Lottery

On Saturday, my neighbors handed me a lotto ticket as a birthday gift. Of course, this was no ordinary lottery ticket; the Powerball had reached the biggest pot ever at nearly one billion dollars. Later that night, I remembered that I had shoved the ticket in my pocket. I had fleeting a moment of joy, where all of a sudden the future seemed wide open. Anything was possible. 

Then, I checked the results. It turned out the only plausible thing occurred, I lost. So did everyone else, and pot for the next lotto increased to well over a billion dollars. Since that moment, I have been more than a little obsessed. 

Even understanding probability as I do, I found myself falling prey to many interesting behavioral phenomena.

Hadoop... There it is (Part 1)

Adventures in building my own personal cloud

Around Silicon Valley, people talk a lot about Moore's Law, which observes that microprocessors double in power (for a constant cost) roughly every 18 months. This law has produced something else that Silicon Valley types talk a lot about: Big Data.

That's right, Big Data did not just pop out of nowhere. As computers have more cheaper and more powerful, the cost of storing data has dropped dramatically. When computers were slow and expensive, people and companies had to make choices about what data to save. Today, its probably more expensive to hire people to spend time thinking about what data to store than it would be to just throw it on a computer somewhere. 

Actually, that last sentence is not quite correct. As powerful a modern computers are, most are not quite big enough to handle Big Data. In fact, the term Big Data defines data that it are too big to store on a single computer. Instead, the data are stored on whole bunch of computers networked together, called a cluster. So I should have said, just throw the data on a bunch of computers somewhere.

Working as a data scientist,  I work on this type of cluster. But I have never actually seen or touched the computers!  In an effort to understand a little bit more about how they work, I decided to build my own personal Big Data computer cluster. 

How I get to work

I know… what could be more self-indulgent and boring to readers than a post about my morning commutes? However, I find myself explaining my commute to tons of people, because it’s pretty interesting. I actually believe that my commute is an interesting example of policy at work. I would also love to find out if anyone has estimated the economic value of my commute. So bear with me, hopefully this is not as self-indulgent as it seems.

Books I am reading in 2016

A list of books, I have read, am reading, will read in 2016

Ranked in approximate order to totally subjective awesomeness.

1.  The Making of The Atomic Bomb, Richard Rhodes
2. The Path to Power (The Years of Lyndon Johnson, Volume 1). Robert A. Caro
3. Just Mercy: A Story of Justice and Redemption. Bryan Stevenson
4. The New Jim Crow: Mass Incarceration in the Age of Colorblindness, Michelle Alexander
5. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, Cathy O'Neil
6. Sapiens: A Brief History of Humankind; Yuval Noah Harari
7. Cryptnomicron, Neal Stephenson
8. What If? Randall Munroe
9. Capital in the Twenty-First Century, Thomas Piketty
10. Yiddush Policemen's Union, Michael Chabon
11. Dream Team: How Michael, Magic, Larry, Charles, and the Greatest Team of All Time Conquered the World and Changed the Game of Basketball Forever; Jack McCallum 
12.  1776. David McCullough
13. Pastrami on Rye: An Overstuffed History of the Jewish Deli. Ted Merwin
14. Six Easy Pieces: Essentials of Physics Explained by Its Most Brilliant Teacher. Richard P. Feynman
15. The Better Angels of Our Nature: Why Violence Has Declined, Steven Pinker
16. Superforcasting: The Art and Science of Prediction; Philip E. Tetlock and Dan Gardner