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gambling « Probability and statistics blog
http://www.statisticsblog.com/category/gambling
Probability and statistics blog. In Monte Carlo We Trust. Mdash; 6 Comments. Wasting away again in Martingaleville. Alright, I better start with an apology for the title of this post. I know, it’s really bad. But let’s get on to the good stuff, or, perhaps more accurately, the really frightening stuff. The plot shown at the top of this post is a simulation of the martingale betting strategy. You’ll find code for it here. What is the martingale betting strategy? Pretty scary, no? Karl Denninger replies...
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charts « Probability and statistics blog
http://www.statisticsblog.com/category/charts
Probability and statistics blog. In Monte Carlo We Trust. Mdash; 9 Comments. Uncovering the Unreliable Friend Distribution. Head down to your local hardware store and pick up a smoke detector. Pop off the cover and look inside. You’ll see a label that mentions Americium 241, a radioactive isotope. Put on your HEV suit. Just how long will you have to wait? And created an exponential timer you can try out for yourself. I would suggest setting it to less than 432 years. Cranking uncertainty up to 11. The lo...
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What’s my daughter listening to? HTML chart gen in R « Probability and statistics blog
http://www.statisticsblog.com/2013/02/whats-my-daughter-listening-to-html-chart-gen-in-r
Probability and statistics blog. In Monte Carlo We Trust. What’s my daughter listening to? HTML chart gen in R. My daughter, who turns 10 in April, has discovered pop music. She’s been listing to Virgin Radio 99.9. One of our local stations. Virgin provides an online playlist. That goes back four days, so I scraped the data and brought it into R. The chart shown at top shows all of the songs played from February 17th through the 20th, listed by frequency. Anyone want to give it a try? Here’s my code.
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games « Probability and statistics blog
http://www.statisticsblog.com/category/games
Probability and statistics blog. In Monte Carlo We Trust. Mdash; 6 Comments. Wasting away again in Martingaleville. Alright, I better start with an apology for the title of this post. I know, it’s really bad. But let’s get on to the good stuff, or, perhaps more accurately, the really frightening stuff. The plot shown at the top of this post is a simulation of the martingale betting strategy. You’ll find code for it here. What is the martingale betting strategy? Pretty scary, no? Karl Denninger replies...
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feature « Probability and statistics blog
http://www.statisticsblog.com/category/feature
Probability and statistics blog. In Monte Carlo We Trust. Mdash; No Comments. Probability Podcast Ep2: Imprecise probabilities with Gert de Cooman. Topics include fair betting rates, Dutch books, Monte Carlo methods, Markov chains, utility, and the foundations of probability theory. We had a rich, wide-ranging discussion. You may need to listen two (or more! Times to process everything. Mdash; 9 Comments. The different approaches of Fermat and Pascal. 3,2) (4,2) (5,2). 3,2) (4,2) (4,3). 3,2) (3,3) (4,3).
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predictions « Probability and statistics blog
http://www.statisticsblog.com/category/predictions
Probability and statistics blog. In Monte Carlo We Trust. Mdash; 7 Comments. Minding the reality gap. Most critically, unemployment excludes the 14 million American on disability benefits, a number which has quadrupled over the last 30 years. If you include just this one segment of the population in the official numbers, the unemployment rate would double. On Saturday, This American Life. Devoted their entire hour to an exploration of this statistic. Discussed the same topic. How metrics go bad. Social m...
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Glossary « Probability and statistics blog
http://www.statisticsblog.com/glossary
Probability and statistics blog. In Monte Carlo We Trust. Knowledge that is with us at the very beginning, based on previous observations or experience. Our initial assumptions are. A number so big you can’t understand it. An experiment performed by generating lots of randomly sampled numbers. Monte Carlo methods can be extremely powerful and are able to simulate processes so convoluted that finding a mathematical equations to describe them would bring a room full of Erdős 2. On Connecting R and Python.
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Manifesto « Probability and statistics blog
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Probability and statistics blog. In Monte Carlo We Trust. Having no useful door to nail these to, I present them here for general public digestion:. Probability is math. Statistics is (applied) epistemology. The biggest questions in statistics revolve around the limits of our knowledge. What conclusions are justified based on which processes? How should we interpret the results of an experiment? When is data bad or good? If your system is chaotic or reflexive, your model must be recursive or iterative.
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Podcast « Probability and statistics blog
http://www.statisticsblog.com/category/podcast
Probability and statistics blog. In Monte Carlo We Trust. Mdash; No Comments. Probability Podcast Ep2: Imprecise probabilities with Gert de Cooman. Topics include fair betting rates, Dutch books, Monte Carlo methods, Markov chains, utility, and the foundations of probability theory. We had a rich, wide-ranging discussion. You may need to listen two (or more! Times to process everything. Mdash; 9 Comments. The different approaches of Fermat and Pascal. 3,2) (4,2) (5,2). 3,2) (4,2) (4,3). 3,2) (3,3) (4,3).
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News « Probability and statistics blog
http://www.statisticsblog.com/category/news
Probability and statistics blog. In Monte Carlo We Trust. Mdash; No Comments. The week in stats (Feb. 24th edition). The Mollusc Shell, created by the R function surf3D. Last Monday (Feb. 17th) was R.A. Fisher’s birthday. To honor him, Deborah G. Mayo, Professor of Philosophy at Virginia Tech, publishes. Fisher and Neyman after anger management,. And RA. Fisher: ‘Two New Properties of Mathematical Likelihood’. Automatically coloring your R output in the terminal using colorout. R: Fun with surf3D function.
