A Ramble Through Probability: How I Learned to Stop Worrying and Love Measure Theory
About this ebook
A Ramble through Probability: How I Learned to Stop Worrying and Love Measure Theory brings together the key elements and applications in a unified presentation aimed at developing intuition; contains an extensive collection of examples that illustrate, explain, and apply the theories; and is supplemented with videos containing commentary and explanations of select proofs on an ancillary website.
This book is intended for graduate students in engineering, mathematics, science, and statistics. Researchers who need to use probability theory will also find it useful.
It is appropriate for graduate-level courses on measure theory and/or probability theory.
About the author
Samopriya Basu is a MITACS Accelerate Postdoctoral Fellow in Statistics at Simon Fraser University, Canada. His research interests include the probabilistic foundations of statistical paradigms and applications to problems in the geophysical sciences and linguistics. He also works on building comparative linguistic databases focusing on under-resourced languages, especially of western North America.
Troy Butler is a professor in the Department of Mathematical and Statistical Sciences at the University of Colorado Denver. In 2023, he began a tour of duty at the National Science Foundation as a rotating Program Director for Computational Mathematics within the Division of Mathematical Sciences. Along with his wife and son, he enjoys practicing mixed martial arts.
Don Estep is Director of the Canadian Statistical Sciences Institute and is the Canada Research Chair in Computational Probability and Uncertainty Quantification (Tier 1) in the Department of Statistics and Actuarial Science at Simon Fraser University. He is also a SIAM Fellow. His research interests include uncertainty quantification for complex physics models, stochastic inverse problems, adaptive computation, and modeling of multiscale systems. Don is an avid hiker and cyclist.
Nishant Panda is a staff scientist in the Information Sciences Group at Los Alamos National Laboratory. His research involves diverse areas of applied mathematics including artificial intelligence, statistical learning, uncertainty quantification, and numerical analysis. When he is not spooked by bears and coyotes, he enjoys long hikes with his dogs in the picturesque trails of northern New Mexico.
