The term "probability" is one that is familiar to us all, though we may use other terms such as "chance", "likelihood", "possibility", and various others.  We ask questions such as "what are the chances it will rain tomorrow", "how likely is it that I will win some money on the lottery", and in all cases what we are after is some measure of how probable the subject of our question is.  In this series of articles, some methods for calculating probabilities are developed and presented, including some examples of problems that can be solved with these methods.

In the first and second articles, basic methods for estimating probabilities are presented, under the assumption of "equally likely outcomes".  The third article looks at conditional probabilities, in the form of Bayes' theorem, and the fourth article provides some worked examples of the theory that is considered in the previous articles.  The final two articles look at some of the classic problems of probability theory, and how they can be solved using the methods presented in the previous articles.

Note that the words and interpretation here are my own.  I have made no attempt at a rigorous treatment of probability theory, and as such have neglected many aspects of the subject.  I have discussed the parts of the theory that interest me, and my aim is only to give a flavour of the theory of probability, and what it is all about.

 

Basic Ideas and Theorems

Counting Events

Bayes' Theorem

Worked Examples

The Game of Craps

The Gambler's Ruin Problem