Excessive wind speeds, inordinately high temperatures of the ocean waters, rotation of the earth, no significant wind shear (cross winds), low atmospheric pressure, the path of the storm, and the geography of the U-shaped coastline all colluded together to make up the intensity of the strongest storm surge to hit land in recorded history. Meteorologists tracking the Pacific storm and a disbelieving public could not have predicted the intensity of the tropical depression turned killer typhoon, Haiyan, as it plowed into the Philippines’ provincial capital, Tacloban, that fateful November day in 2013. The typhoon’s penultimate, 20-foot, storm surge went off the charts with sustained wind speeds of 200 mph as it met the coastline. It was classified as an 8.08 (170 Knots or 195 mi/hr wind speed with gusts up to 240 mi/hr) storm on the Dvorak scale, a number which exceeded the scale’s maximum value of 8.
With world-wide climate changes and rising sea temperatures and levels, scientists and mathematicians are challenged to create a predictive model of tropical storm surges which can help us prepare for future monster storms so as to save lives and create more protective landscapes along the coastal waters of the planet.
For a scientific account and very human story of this storm, see: One of the Deadliest Typhoons published by Geographic TV on September 22, 2015.
(published by the World Science Festival on January 7, 2015)
Is our intuition or extra sensory perception a reasonably reliable source for decision making? How well do our “gut feelings” measure up to the cold reality of factual information? Do our innate, mental patterns of processing information emulate statistical Bayesian processes?
Find out the opinions of a panel of five academic experts who regularly grapple with the complexities of statistical information and how to interpret data properly, who critically examine how decisions are made in the public arenas of medicine and law, and who analyze the neurological, cognitive processes of the human mind.
MODERATOR: Marcus du Sautoy, Professor of Mathematics at the University of Oxford, England
Gerd Gigerenzer, Director of the Max Plank Institute for Human Development in Berlin, Germany
Leonard Mlodinow, physicist and author of a number of books including The Drunkard’s Walk: how randomness rules our lives, which has been described as a readable course in randomness and statistics
Josh Tenenbaum, Professor of Computational Cognitive Science in the Department of Brain and Cognitive Sciences at MIT (Massachusetts Institute of Technology)
Amir Aczel, a mathematician and science writer, one of whose books is entitled, Chance, and is described by the New York Times as an edifying and amusing guide to the basic elements of probability theory.
Since the time of Joseph Bell (1837 – 1911), forensic science began to be instrumental in the solving of numerous crimes, including murder cases. Dr. Bell, both a lecturer at the medical school of the University of Edinburgh and a surgeon at the Royal Infirmary of Edinburgh, is considered to be a pioneer in the subject of forensic pathology. Also of interest is that Arthur Conan Doyle, creator of the Sherlock Holmes series of detective stores, had worked for Bell as a clerk during his student days. It is widely believed that Dr. Bell was the prototype for Doyle’s famous fictional sleuth.
Today, over a century later, finger prints, blood spatter patterns, ballistics, residual drug levels in body tissues, and DNA are most often the techniques which collude to glue together a crime scene into an indictable offense with the sole purpose of bringing the perpetrator(s) to justice. However, have you ever heard of using mathematics and astronomy in a court room to tear apart a killer’s seemly rock solid alibi at the time of the murder?
Check out the following true crime story: Solved: Truth in Shadows to uncover the hidden reality behind a murder mystery where there were no eye witnesses except the killer …….. and the sun.
by Peter Crickmore
This is an introduction to fuzzy sets, fuzzy functions, fuzzy arithmetic, and fuzzy logic with fuzzy applications towards environmental concerns. Moreover, these concepts and ideas lead to Possibility Theory instead of Probability Theory and how they are related.
For those who think this is a piece of someone's fuzzy imagination, take a look and judge for yourself.
by Peter Crickmore
A presentation on how to design field experiments to yield the most information from the fewest runs. Prediction variances and confidence intervals come into play in the analysis of the experiments.
by Peter Crickmore
A discussion on confidence intervals and what is considered to be 'significant' in the oil patch.
Updated December 13 2016 by Student & Academic Services