Discrete Distribution

Binomial Distribution

\[Pr(X=x)=\binom{n}{x}p^x{(1-p)}^{n-x}\]

Bernoulli Distribution

A Bernoulli distribution is a special case of binomial distribution. Specifically, when n=1, i.e. x only could be 0 or 1, the binomial distribution becomes Bernoulli distribution.

Geometric Distribution

The geometric distribution gives the probability that the first occurrence of success requires k independent trials, each with success probability p. If the probability of success on each trial is p, then the probability that the kth trial (out of k trials) is the first success is

\[Pr(X=x)=(1-p)^{x-1}p\]

Poisson Distribution

Poisson distribution is a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time.

\[\begin{split}Pr(X=x)=\frac{\lambda^x e^{-\lambda}}{x!}, \\ \lambda = E(X) = Var(X)\end{split}\]

Continuous Distribution

Uniform Distribution

\[Pr(X=x) = \frac{1}{n}\]

Normal Distribution

i.e. Gaussian distribution

\[Pr(X=x)={\frac {1}{\sigma {\sqrt {2\pi }}}}e^{-{\frac {1}{2}}\left({\frac {x-\mu }{\sigma }}\right)^{2}}\]

Exponential Distribution