The Art of Insight in Science and Engineering
Sanjoy Mahajan
The Art of Insight in Science and Engineering
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In this book, Sanjoy Mahajan shows us that the way to master complexity is through insight rather than precision. Precision can overwhelm us with information, whereas insight connects seemingly disparate pieces of information into a simple picture. Unlike computers, humans depend on insight. Based on the author’s fifteen years of teaching at MIT, Cambridge University, and Olin College, The Art of Insight in Science and Engineering shows us how to build insight and find understanding, giving readers tools to help them solve any problem in science and engineering.



To master complexity, we can organize it or discard it. The Art of Insight in Science and Engineeringfirst teaches the tools for organizing complexity, then distinguishes the two paths for discarding complexity: with and without loss of information. Questions and problems throughout the text help readers master and apply these groups of tools. Armed with this three-part toolchest, and without complicated mathematics, readers can estimate the flight range of birds and planes and the strength of chemical bonds, understand the physics of pianos and xylophones, and explain why skies are blue and sunsets are red.

Print editions available from MIT Press.

Language
English
ISBN
Unknown
Brief Contents
Preface
Values for Backs of Envelopes
Part I: Organizing Complexity
1 Divide and conquer
2 Abstraction
Part II: Discarding Complexity Without Losing Information
3 Symmetry and Conservation
4 Proportional Reasoning
5 Dimensions
Part III: Discarding Complexity with Loss of Information
6 Lumping
7 Probabilistic Reasoning
8 Easy Cases
9 Spring Models
Bon Voyage: Long-Lasting Learning
Bibliography
Index
Contents
Preface
Values for Backs of Envelopes
Part I: Organizing Complexity
Divide and Conquer
2 Abstraction
Part II: Discarding Complexity Without Losing Information
3 Symmetry and Conservation
4 Proportional Reasoning
5 Dimensions
Part III: Discarding Complexity with Loss of Information
6 Lumping
7 Probabilistic Reasoning
8 Easy Cases
9 Spring Models
Bon Voyage: Long-lasting Learning
Bibliography
Index
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