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Street-Fighting Mathematics: The Art of Educated Guessing and Opportunistic Problem Solving
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  • Title: Street-Fighting Mathematics: The Art of Educated Guessing and Opportunistic Problem Solving
  • Author(s) Sanjoy Mahajan
  • Publisher: The MIT Press; New edition (March 5, 2010)
  • License(s): CC BY-NC-SA 3.0 US
  • Paperback: 152 pages
  • eBook: PDF (153 pages)
  • Language: English
  • ISBN-10: 026251429X
  • ISBN-13: 978-0262514293
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Book Description

This engaging book is an antidote to the rigor mortis brought on by too much mathematical rigor, teaching us how to guess answers without needing a proof or an exact calculation.

In problem solving, as in street fighting, rules are for fools: do whatever works--don't just stand there! Yet we often fear an unjustified leap even though it may land us on a correct result. Traditional mathematics teaching is largely about solving exactly stated problems exactly, yet life often hands us partly defined problems needing only moderately accurate solutions.

In Street-Fighting Mathematics, Sanjoy Mahajan builds, sharpens, and demonstrates tools for educated guessing and down-and-dirty, opportunistic problem solving across diverse fields of knowledge - from mathematics to management. Mahajan describes six tools: dimensional analysis, easy cases, lumping, picture proofs, successive approximation, and reasoning by analogy.

Illustrating each tool with numerous examples, he carefully separates the tool - the general principle - from the particular application so that the reader can most easily grasp the tool itself to use on problems of particular interest.

Street-Fighting Mathematics grew out of a short course taught by the author at MIT for students ranging from first-year undergraduates to graduate students ready for careers in physics, mathematics, management, electrical engineering, computer science, and biology. They benefited from an approach that avoided rigor and taught them how to use mathematics to solve real problems.

About the Authors
  • Sanjoy Mahajan studied mathematics at the University of Oxford and received a PhD in theoretical physics at the California Institute of Technology. He is now Associate Director of the Teaching and Learning Laboratory and a Lecturer in the Department of Electrical Engineering and Computer Science at MIT. Before coming to MIT, he was a Fellow of Corpus Christi College, Cambridge, and a Lecturer in Physics in the University of Cambridge.
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