12/22/2018 0 Comments Decision Making and Chance Part1SADIK: We're very pleased to have Dr. Michael Orkin here to give us a talk today. Dr. Michael Orkin has a very distinguished career. He's currently Managing Scientist at the Exponent, a publicly traded center scientific consulting company here in Menlo Park. He's a well-known personality. He's been nationally quoted, CNN, NBC's Dateline and ABC World News.
He's written several books, including What are the Odds? : A Chance In Everyday Life. He's consulted for clients in both government and private sector, including the FBI, and Las Vegas odds makers. His software has also been featured in the January 2002 issue of Wired magazine. So here he is today. Let's give a Google welcome to Mike. Could I please ask that because this talk is being video recorded, any confidential Google questions should be left till after the cameras have been switched off. Thank you. [APPLAUSE] DR. MICHAEL ORKIN: Thanks, Sadik. So today-- well, the title of my talk-- and I'm happy to be here-- is Chance, Data Mining, and Sports Betting, and we'll see what those things have in common. I am currently located at Exponent. If you haven't heard of it, it's sometimes called Exponent Failure Analysis. It's located right on 101 North in Menlo Park. It's a publicly traded company that has about 800 employees, in 18 offices and three international offices. Consultants at Exponent, a majority of whom are engineers, have expertise in science, math, and engineering. And Exponent has been consulted on various problems and disasters, including some of the major ones you read about in the paper, such as the grounding of the Exxon Valdez, the walkway collapse of the Kansas City Hyatt, the bombing of the Alfred P. Murrah Federal building in Oklahoma City. By the way, in this talk, just stop me at any time if you have any questions, and we'll have more of a conversational tone. So I'm in what's called the data and risk analysis group. I'm trained as a statistician, and do stuff in probability theory, decision theory, game theory. And our group develops strategies for decision-making under uncertainty, and in a variety of contexts. One of the things our group specializes in is determining whether a particular activity or product poses an unreasonable risk, and if so, what to do about it. Many of our projects involve litigation involving such things as consumer product issues and recalls. Automotive lawsuits, and doing risk analyses and failure analyses to try to develop strategies for companies who have products. I can't really to go into too much detail about things that are in litigation right now. But that's not what I want to talk about anyway. I want to talk about one of my specialties, which is chance and gambling games. I'll actually be talking about actually a case that is an Exponent case, along with some software and things that are not Exponent things, just things I've done. So first, this a little primer on gambling. So roulette-- how many of you have been to a casino and have seen a roulette wheel. Most of you. So roulette's a pretty simple game to understand. There are 38 sections labeled from 1 to 36 along with a zero and a double zero. And half of the sections from 1 to 36 are red, half are black, zero and double zero are green. You can bet on a color, you can bet on a combination of numbers, you can make varieties of bets at the roulette table. One of the bets is number 17. In other words, you put some chips on number 17. The wheel is spun, the ball is dropped in, 17-- the ball lands in the slot marked 17. You win. Otherwise you lose. And since there are 38 sections on the wheel, your chance of winning is 1 in 38. If you bet on red, since there are 18 red sections out of 38, your chance of winning is 18 out of 38. So you're much more likely to win a red bet than you are a bet on number 17. So to get people to make this bet, what does the casino have to do? They have to offer higher payoff odds. So the payoff odds for this bet, a bet on a particular number, are 35:1. That means if you bet $1 and number 17 comes up, you'll make a $35 profit. You'll get your dollar chip back plus another 35. Well, there's a mathematical theorem called the law of averages. It's just called the law of large numbers by mathematicians. It says that if you repeat an experiment independently over and over again, the fraction of times that something comes up will be the same as the probability of it happening in one trial. So the probability of it happening in one trial on this bet is 1 in 38, so you don't know what's going to happen in one bet or two bets or a few bets, but in repeated bets you'll win an average of 1 in 38, and lose an average of 37 for a net loss of $2. So that's $2 and $38 bet, which becomes 5.3% profit for the house, the house being the casino. So that's called the house edge in roulette. And it's very straightforward, cut and dry math. This is what happens if you repeatedly make a bet in roulette. Like I said, you can get lucky, you can get unlucky and lose sooner than at this rate, or you can win and quit. But in repeated play, you will eventually lose and go broke at roughly the rate of 5.3 cents per dollar bet. Sooner if you have a losing streak. So that's sort of the facts on betting on number 17 in roulette, and in fact, in making just about any roulette bet, or a combination of roulette bets, or other betting strategy applied to roulette. So you can show mathematically that this is what happens, period. For instance, people use some sort of sophisticated strategies, like double your money if you lose, and keep going until you eventually win. You've heard that one, the doubld-up strategy.
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