Tag continuous

Extreme Value Distribution

For Weibull, let \(Y=\ln(X)\). This has both scale and location parameters. Location is \(\theta_{1}=\ln(\beta)\) and scale is...

The Beta Distribution

The beta distribution The parameters are \(\alpha,\beta>0\), and \(A,B\) with \(B\ge A\). \begin{equation*}...

The Lognormal Distribution

If \(Y=\ln X\) is a normal distribution, then \(X\) is log-normal. \begin{equation*} f(x;\mu,\sigma)=\frac{1}{\sqrt{2\pi\sigma}...

The Weibull Distribution

Probability Density Function Let \(\alpha,\beta>0\) \begin{equation*}...

The Erlang Distribution

If the time between successive events is independent each with an exponential distribution with \(\lambda\), then the total time \(X\)...

The Chi-Squared Distribution

Chi-squared distribution Probability Density Function The parameter is \(\nu\) and it is a positive integer. It is the gamma...

The Exponential Distribution

Exponential distribution Probability Density Function Let \(\lambda>0\) \begin{equation*} f(x;\lambda)=\lambda e^{-\lambda x}...

The Gamma Distribution

The problem with the normal distribution is that it is symmetric. The Gamma distribution is useful for skewed distributions....

The Normal Distribution

Probability Distribution Function The parameters are \(-\infty<\mu<\infty\) and \(\sigma>0\). \begin{equation*}...

Pareto Distribution

The Pareto distribution is good for approximating income distributions or population sizes. The pdf is given by: \begin{equation*}...

Continuous Random Variables and Probability Distributions

Continuous distributions are given by a probability density function (pdf): \begin{equation*} P\left(a\le X\le...