Betting has had a long and close relationship with the science of probability and statistics. In the mid-1600’s, the French intellectual and gambler Antoine Gombaud, who called himself Chevalier de Méré, enlisted the help of the mathematician Blaise Pascal to solve several puzzles involving dice games. Pascal’s ensuing work is regarded as the foundation ofContinue reading “Betting and Statistics”
Monthly Archives: November 2019
Operations Research (O/R) For Sewage
Older urban sewer systems are not sealed, dedicated route networks leading to sewage treatment plants. Rather, to save money when they were built decades ago, in some places they shared pipes with storm water drainage systems that lead to creeks, rivers and bays. As a result, when stormwater inundates the system, it carries with itContinue reading “Operations Research (O/R) For Sewage”
Nov 25: Statistics in Practice
In this week’s Brief, we take a look at the history of betting and how it is entwined with probabilistic decision-making. Probabilistic decision-making is also the focus of our 3-course Optimization Mastery, which covers linear programming, integer programming, simulation and other operations research (O/R) techniques. Start with: Jan 3 – 31: Optimization – Linear Programming See youContinue reading “Nov 25: Statistics in Practice”
Errors and Loss
Errors – differences between predicted values and actual values, also called residuals – are a key part of statistical models. They form the raw material for various metrics of predictive model performance (accuracy, precision, recall, lift, etc.), and also the basis for diagnostics on descriptive models. A related concept is loss, which is some functionContinue reading “Errors and Loss”
Unforeseen Consequences in Data Science
Unforeseen Consequences in Data Science After the massive Exxon Valdez oil spill, states passed laws boosting the liability of tanker companies for future spills. The result was not as intended: fly-by-night companies, whose bankruptcy would not be consequential, took over the trade. In this blog we look at some notable examples of unforeseen consequences ofContinue reading “Unforeseen Consequences in Data Science”