This week we look at several ways to fool yourself, statistically – variants of the “Gambler’s Fallacy.” Gambling is all about accurately assessing risk, so, naturally, our featured course is:
- Nov 15 – Dec 13: Risk Simulation and Queuing
See you in class!
– Peter Bruce,
Chief Academic Officer, Author, Instructor, and Founder
The Institute for Statistics Education at Statistics.com
Statistical Thinking
Gambler’s Fallacy
Is a baseball umpire judging a close pitch less likely to call a strike if he has called the two previous pitches strikes? More likely? Learn which, and how the Gambler’s Fallacy plays a role […]
Word of the Week
Latin hypercube
In Monte Carlo sampling for simulation problems, random values are generated from a probability distribution deemed appropriate for a given scenario (uniform, poisson, exponential, etc.). Latin hypercube sampling, in contrast to simple random sampling, […]
Historical Spotlight
Gambler’s Fallacy I at Monte Carlo
On August 18, 1913, at the famous casino in Monte Carlo, Monaco, the roulette ball fell black 26 times in a row. Gamblers, seeing the streak grow, increasingly shifted their bets to red, feeling that an excess of reds was due, to counterbalance the remarkable black streak. They lost millions.
Quote
Realism on Risk
Risk is a favorite topic for quotes. Nearly 100% of these quotes are from people who were successful in taking risks, and the quotes take a romantic and motivational view of risk. They encourage people to take risks, that being the only way to learn and accomplish something worthwhile. Richard Branson, founder of the various Virgin airline and aerospace ventures, has his own list, liberally illustrated with photos of Branson on a tightrope, Branson leaning out of a cockpit, Branson gazing contemplatively into the distance from a mountaintop.
Very few take a more balanced and realistic view; here is one:
“When forecasting the outcomes of risky projects, executives too easily fall victim to the planning fallacy. In its grip, they make decisions based on delusional optimism rather than on a rational weighting of gains, losses and probabilities.”
Daniel Kahneman, Thinking Fast and Slow
Course Spotlight
Nov 15 – Dec 13: Risk Simulation and Queuing
In this course, you will use Excel-based simulation software to:
- Construct and implement simulation models to model the uncertainty in decision input variables (e.g. price, demand, etc.), so that the overall estimate of interest from a model can be supplemented by a risk interval
- Construct and implement queuing models to model the variability in arrivals over time (customers at a service desk, cars at a toll plaza, data packets, etc.) and ensuing queues
- Use decision trees to incorporate information derived from models to actually make optimal decisions.
Your instructor is Cliff Ragsdale, Professor of Business Information Technology at Virginia Tech University and author of the best-selling text Spreadsheet Modeling and Decision Analysis.
See you in class!
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