Overview

Based around a series of real-life scenarios, this engaging introduction to statistical reasoning will teach you how to apply powerful statistical, qualitative and probabilistic tools in a technical context. From analysis of electricity bills, baseball statistics, and stock market fluctuations, through to profound questions about physics of fermions and bosons, decaying nuclei, and climate change, each chapter introduces relevant physical, statistical and mathematical principles step-by-step in an engaging narrative style, helping to develop practical proficiency in the use of probability and statistical reasoning. With numerous illustrations making it easy to focus on the most important information, this insightful book is perfect for students and researchers of any discipline interested in the interwoven tapestry of probability, statistics, and physics.

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9781107032811

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Reviews

'For physicists, it has long been integral to our science to ascribe an uncertainty to every data point, to every inference, to every theory. That is, a measurement is regarded as meaningless without assigning an 'error bar' to it. This delightful book by Mark Silverman shows the reader how a physicist does this with the 'tools of his trade'; namely mathematical analysis, starting with Bayes' theorem, Poissonian and Gaussian statistics, and progressing through Shannon's information formulation of entropy. This book is mathematically complete, but not intense, making it intellectually stimulating, with conclusions that are sometimes surprising. I recommend it with considerable enthusiasm.' Samuel A. Werner, University of Missouri 'A Certain Uncertainty is a 'case study' approach that gives insight in the proper use of statistics through truly interesting physics. This is a book you will read, enjoy, and keep.' James P. McClymer, University of Maine

'For physicists, it has long been integral to our science to ascribe an uncertainty to every data point, to every inference, to every theory. That is, a measurement is regarded as meaningless without assigning an 'error bar' to it. This delightful book by Mark Silverman shows the reader how a physicist does this with the 'tools of his trade'; namely mathematical analysis, starting with Bayes' theorem, Poissonian and Gaussian statistics, and progressing through Shannon's information formulation of entropy. This book is mathematically complete, but not intense, making it intellectually stimulating, with conclusions that are sometimes surprising. I recommend it with considerable enthusiasm.' Samuel A. Werner, University of Missouri

Author Information

Mark P. Silverman is the G. A. Jarvis Professor of Physics at Trinity College, Connecticut. He received his PhD in Chemical Physics from Harvard University, and has since pursued a wide range of experimental and theoretical studies concerning the structure of matter, the behavior of light, and the dynamics of stars and galaxies.

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