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Revision as of 05:25, 5 April 2012

This Collective table of formulas is proudly sponsored
by the Nice Guys of Eta Kappa Nu.

Visit us at the HKN Lounge in EE24 for hot coffee and fresh bagels only $1 each!

                                         HKNlogo.jpg
Probability Formulas
Properties of Probability Functions
The complement of an event A (i.e. the event A not occurring) $ \,P(A^c) = 1 - P(A)\, $
The intersection of two independent events A and B $ \,P(A \mbox{ and }B) = P(A \cap B) = P(A) P(B)\, $
The union of two events A and B (i.e. either A or B occurring) $ \,P(A \mbox{ or } B) = P(A) + P(B) - P(A \mbox{ and } B)\, $
The union of two mutually exclusive events A and B $ \,P(A \mbox{ or } B) = P(A \cup B)= P(A) + P(B)\, $
Event A occurs given that event B has occurred $ \,P(A \mid B) = \frac{P(A \cap B)}{P(B)}\, $
Total Probability Law $ \,P(B) = P(B|A_1)P(A_1) + \dots + P(B|A_n)P(A_n)\, $
$  \mbox{ where } \{A_1,\dots,A_n\} \mbox{ is a partition of sample space } S, B \mbox{ is an event }. $
Bayes Theorem $ \,P(A_j|B) = \frac{P(B|A_j)P(A_j)}{\sum_{i=1}^{n}P(B|A_i)P(A_i)},\ \{A_i\} \mbox{ and } B \mbox{ are as above }. $
Expectation and Variance of Random Variables
Binomial random variable with parameters n and p $ \,E[X] = np,\ \ Var(X) = np(1-p)\, $
Poisson random variable with parameter $ \lambda $ $ \,E[X] = \lambda,\ \ Var(X) = \lambda\, $
Geometric random variable with parameter p $ \,E[X] = \frac{1}{p},\ \ Var(X) = \frac{1-p}{p^2}\, $
Uniform random variable over (a,b) $ \,E[X] = \frac{a+b}{2},\ \ Var(X) = \frac{(b-a)^2}{12}\, $
Gaussian random variable with parameter $ \mu \mbox{ and } \sigma^2 $ $ \,E[X] = \mu,\ \ Var(X) = \sigma^2\, $
Exponential random variable with parameter $ \lambda $ $ \,E[X] = \frac{1}{\lambda},\ \ Var(X) = \frac{1}{\lambda^2}\, $

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Sean Hu, ECE PhD 2009