Jump to ratings and reviews
Rate this book

Mathematics and Plausible Reasoning #2

Patterns of Plausible Inference

Rate this book
A guide to the practical art of plausible reasoning, this book has relevance in every field of intellectual activity. Professor Polya, a world-famous mathematician from Stanford University, uses mathematics to show how hunches and guesses play an important part in even the most rigorously deductive science. He explains how solutions to problems can be guessed at; good guessing is often more important than rigorous deduction in finding correct solutions. Vol. II, on Patterns of Plausible Inference , attempts to develop a logic of plausibility. What makes some evidence stronger and some weaker? How does one seek evidence that will make a suspected truth more probable? These questions involve philosophy and psychology as well as mathematics.

200 pages, Paperback

First published January 1, 1954

8 people are currently reading
423 people want to read

About the author

George Pólya

71 books180 followers

Ratings & Reviews

What do you think?
Rate this book

Friends & Following

Create a free account to discover what your friends think of this book!

Community Reviews

5 stars
33 (62%)
4 stars
14 (26%)
3 stars
6 (11%)
2 stars
0 (0%)
1 star
0 (0%)
Displaying 1 - 2 of 2 reviews
Profile Image for Eugene Shcherbinin.
21 reviews1 follower
February 21, 2024
what a great book! Really enjoyed how it gives a very intuitive introduction to both frequentist and Bayesian approach to probability and applies it in a very wise manner to a diversity of problem-solving issues. I think I myself started thinking in categories of plausibility evaluating, for example, results I obtain in further mathematical methods problems
Profile Image for Sarah Wise.
24 reviews1 follower
June 5, 2025
In defense of subjective probability. I’ve been pondering the phenomenon, and it goes something like this: we go through university being taught a frequentist perspective, which involves deriving hypotheses from data collected, accepting or rejecting the null hypothesis, and accumulating information. But what if there is another perspective which does not deal with data as a prior, as a given set from which you deduct your hypothesis? This is the logic of plausible reasoning. It's uncomfortable from the frequentist point of view. How do you determine the priors? Who is to say if they are correct? biased? is it too subjective? . . . Here, Polya argues poetically for the potential for plausible reasoning to have rigour and leverage subjectivity. I think this is an incredible book. I highly recommend it if you are interested in Bayesianism or conditional probability.
Displaying 1 - 2 of 2 reviews

Can't find what you're looking for?

Get help and learn more about the design.