# Metropolis-Hastings Algorithm / Metropolis Algorithm

Markov Chain Monte Carlo > The Metropolis-Hastings algorithm is one of many sampling algorithms that belong to the general Markov Chain Monte Carlo class of algorithms. One of the simplest types of MCMC algorithms, it was named for Metropolis et…

# Bayesian Statistics, Inference, and Probability

Probability and Statistics > Contents: What is Bayesian Statistics? Bayesian vs. Frequentist Important Concepts in Bayesian Statistics Related Articles 1. What is Bayesian Statistics? Bayesian statistics (sometimes called Bayesian inference) is a general approach to statistics which uses prior probabilities…

# Chinese Restaurant Process: Simple Definition & Example

Dirichlet process > The Chinese Restaurant Process is a metaphorical way for how a Dirichlet process generates data. The Dirichlet process models randomness of a probability mass function (PMF) with unlimited options (e.g. an unlimited amount of dice in a…

# Bell’s Numbers and the Bell Triangle

Statistics Definitions > Bell’s numbers Bell’s Numbers and the Bell Triangle (sometimes called the Pierce triangle or Aitken’s array) are a sequence of numbers which count the possible partitions of a set, and the triangle which makes derivation of them…

# Jeffreys Prior / Jeffreys Rule Prior: Simple Definition

Statistics Definitions > Jeffrey’s prior (also called Jeffreys-Rule Prior), named after English mathematician Sir Harold Jeffreys, is used in Bayesian parameter estimation. It is an uninformative prior, which means that it gives you vague information about probabilities. It’s usually used…

# Hierarchical Model: Definition

Statistics Definitions > A hierarchical model is a model in which lower levels are sorted under a hierarchy of successively higher-level units. Data is grouped into clusters at one or more levels, and the influence of the clusters on the…

# Radar Chart: Simple Definition, Examples

Descriptive Statistics > A radar chart is a 2D chart presenting multivariate data by giving each variable an axis and plotting the data as a polygonal shape over all axes. All axes have the same origin, and the relative position…

# Free Parameter: Definition, Examples

Statistics Definitions > A free parameter is one which is not pre-defined by the model, but which can be chosen or estimated based on theoretical ideas or experimental data. Other types of parameters include fixed and constrained. Fixed parameters are…

# Defect Concentration Diagram: Definition, Examples

Statistical Process Control > A defect concentration diagram is a visual representation—usually, a diagram or map—which shows all defects or problem areas in what is being analyzed. As a research tool, it may began as a blank diagram or picture,…

# Contingency Coefficient: Definition

Coefficient of Association > The contingency coefficient is a coefficient of association that tells whether two variables or data sets are independent or dependent of each other. It is also known as Pearson’s Coefficient (not to be confused with Pearson’s…