trying to introduce people to Bayesian reasoning is that the existing online explanations are too abstract. Bayesian reasoning is very counterintuitive. People do not employ Bayesian reasoning intuitively, find it very difficult to learn Bayesian reason
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a portable command-line driven interactive data and function plotting utility for UNIX, IBM OS/2, MS Windows, DOS, Macintosh, VMS, Atari and many other platforms.
Following the success of last season, my thoughts obviously turned to whether this can be repeated. Or more accurately, what can be expected from the algorithm betting model in future seasons both in terms of return and the variability of those returns. “Monte Carlo” is the name given to simulations which make use of computer generated random numbers to identify the range of possible outputs a model may generate in the ‘real world’. Each random number generates an input from a user defined probability distribution which is run through the user’s model to produce a simulated outcome on each run. Run this simulation thousands of times and you generate a probability distribution for the output of your model. Assigning a probability distribution to football match results
Web site for statistical computation; probability; linear correlation and regression; chi-square; t-procedures; t-tests; analysis of variance; ANOVA; analysis of covariance; ANCOVA; parametric; nonparametric; binomial; normal distribution; Poisson distribution; Fisher exact; Mann-Whitney; Wilcoxon; Kruskal-Wallis; Richard Lowry, Vassar College
This is code implements the example given in pages 11-15 of An Introduction to the Kalman Filter by Greg Welch and Gary Bishop, University of North Carolina at Chapel Hill, Department of Computer Science.
Hal Varian, Google’s Chief Economist, was interviewed a few months ago, and said the following in the McKinsey Quarterly: “The sexy job in the next ten years will be statisticians… The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill.”
With Open Source now considered an accepted part of the software industry, some people are starting to wonder if we can't bring the same degree of openness and innovation into government. Danese Cooper, who is actively involved in the open source community through her work with the Open Source Initiative and Apache, as well as working as an R wonk for Revolution Computing, would love to see the government become more open. Part of that openness is being able to access and interpret the mass of data that the government collects, something Cooper thinks R would be a great tool for. She'll be talking about R and Open Government at OSCON, the O'Reilly Open Source Convention.
REvolution Computing offers REvolution R, an enhanced distribution of R, as a free download. It also offers REvolution R Enterprise, a subscription-based version of R aimed at large companies that work with large data sets, and ParallelR (included in the Enterprise edition), which can take advantage of multi-processor systems and clusters for large data crunching tasks. R itself, and REvolution's versions, are being embraced in a number of fields, with a number of innovative new applications arriving.
FreeMat is a free environment for rapid engineering and scientific prototyping and data processing. It is similar to commercial systems such as MATLAB from Mathworks, and IDL from Research Systems, but is Open Source. FreeMat is available under the GPL license.
# R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. To download R, please choose your preferred CRAN mirror. # If you have questions about R like how to do