Introduction

Probability can be classified into two categories: Physical and Evidential. Physical probability i salso referred to as objective or frequenta
and is usually associated with a random physical system. Evidentia probability also known as Bayesian probabililty is associated with
any statement. This leads to what is called subjective plausibility. There are two classical definitions for probability. The first, given by Laplace in 1812 is given by

(1)
\begin{align} P(A)=\frac{N_{A}}{N} \end{align}

where $A$ is an event, $P(A)$ is the probability of event $A$, $N_{A}$ is the number of times that event $A$ occurs, and $N$ is the number of all possible outcomes. The second definition stems from frequentism. It is based on the concept that a probability is a measure of how frequent an event occurs over a long period of time. This is written as:

(2)
\begin{align} P(A)=\lim_{N\to\infty}\frac{N_{A}}{N} \end{align}

Finally, one can define a logical probability as Evidence $E$ supports hypothesis $H$ to a high degree. This is also known as epistemic or inductive probability.

page revision: 5, last edited: 25 Nov 2010 04:17