Name: Fifty challenging problems in probability
ISBN: 9780486653556

Fifty challenging problems in probability

Can you solve the problem of "The Unfair Subway?" Marvin gets off work at random times between 3 and 5 p.m. His mother lives uptown, his girl friend downtown. He takes the first subway that comes in either direction and eats dinner with the one he is first delivered to. his mother complains that he has never come to see her, but he says she has a 50-50 chance. He has had dinner with her twice in the last 20 working days. Explain. Marvin's adventures in probability are one of fifty intriguing puzzlers that illustrate both elementary and advanced aspects of probability, each problem designed to challenge the mathematically inclined. From "The Flippant Juror" and "The Prisoner's Dilemma" to "The Cliffhanger" and "The Clumsy Chemist," they provide an ideal supplement to courses in probability and statistics as well as a lively source of amusement for all who enjoy the stimulating fun of mathematics. Professor Frederick Mosteller, who teaches statistics at Harvard University, has chosen the problems for originality, general interest or because they demonstrate valuable techniques. In addition, the problems are graded as to difficulty and many have considerable stature. Indeed, one has "enlivened the research lives of many excellent mathematicians." Detailed solutions are included. There is every probability you'll need at least a few of them. -- from back cover.

What Hacker News says

Al0neStarDec 2024

These books are what i would consider the best books for self-study. (I have gone through many textbooks after i went back to school to study statistics.)

• Real Analysis: A Long-Form Mathematics Textbook

• Proofs: A Long-Form Mathematics Textbook

• Mathematical Logic Through Python

• A Course in Calculus and Real Analysis

• A Course in Multivariable Calculus and Analysis

• Differential Equations With Applications and Historical Notes

• Probability and Random Processes (Grimmet)

• Probability Through Problems

• Fifty Challenging Problems in Probability with Solutions

• The Simple and Infinite Joy of Mathematical Statistics

• An Introduction to Error Analysis

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charlescearlFeb 2021

Thanks for the reference. Another algorithms text -- though Haskell centric -- that provides solutions is Algorithm Design With Haskell [1]. The exhaustive Combinatorial Mathematics by Douglas West [2] provides hints at least. These are advanced texts though. Another source of solved problems are "problems in" books. Dover offers affordable titles like Fifty Challenging Problems in Probability [3]. There are other classics like Combinatorial Problems and Exercises [4] or Proofs from the Book [5], all with solved exercises.

[1] https://www.cambridge.org/core/books/algorithm-design-with-h...

[2] https://faculty.math.illinois.edu/~west/

[3] https://store.doverpublications.com/0486653552.html

[4] https://www.ams.org/books/chel/361/

[5] https://www.springer.com/gp/book/9783642008566

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NWChenNov 2018

Ch. 1-5 of Sheldon Ross's "A First Course in Probability" works for this purpose. Consider testing/hardening your knowledge with Mosteller's "Fifty Challenging Problems in Probability".

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Q4273j3bSep 2013

Basic prob & stats:

1. _Stats: Data and Models_ by De Veaux, Velleman & Bock

2. _Fifty Challenging Problems in Probability with Solutions_ by Mosteller

3. http://yudkowsky.net/rational/bayes

Basic data analysis:

1. _Python for Data Analysis_ by Wes McKinney

2. http://camdavidsonpilon.github.io/Probabilistic-Programming-...

3. _Exploratory Data Analysis_ by Tukey

4. _The Visual Display of Quantitative Information_ by Tufte

Tools:

- R & ggplot2 & (Sweave | knitR)

- Python & numpy & pandas

- UNIX tools (https://news.ycombinator.com/item?id=6046682, https://news.ycombinator.com/item?id=6412190)

- basic SQL (https://schemaverse.com/tutorial/tutorial.php)

- data visualization: (R & ggplot2) | (Python & matplotlib) | d3.js

- OPTIONAL: C/C++/Java for hardcore Bayesian stuff, Julia for being cool, Fortran for specific academic domains

On getting people to take you seriously: If you knew the stuff up there, I would take you very seriously, even without the STEM degree. You can pick this stuff up outside the classroom (in fact it might be hard to find uni classes that cover this stuff). So if you did self-study, and blogged about it or something, people would take you seriously (esp. if you got good at something "hot" like d3.js or Bayesian). In fact, given your background in web / software / business, you could be considered even more valuable (by web / software / business people).

What are you interested in specifically? Where do you want to end up?

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