Statistics Definitions > The Bertrand Paradox is a prime example of how two words—”random” and “equal probability” are incorrectly used to mean the same thing. The paradox shows that if you don’t define your probabilities well, then the mechanism that…

## Asymptotic Normality

Statistics Definitions > Asymptotic normality is a property of an estimator. “Asymptotic” refers to how an estimator behaves as the sample size gets larger (i.e. tends to infinity). “Normality” refers to the normal distribution, so an estimator that is asymptotically…

## Dagum Distribution: Definition, CDF & PDF

Probability Distributions > The Dagum distribution (also called the Inverse Burr distribution; Dagum called it the generalized logistic-Burr distribution) was proposed by Camilo Dagum in the 1970s to model income and wealth distribution. Dagum developed the models as an alternative…

## Complete Statistic: Definition

Statistics Definitions > A complete statistic T “… is a complete statistic if the family of probability densities {g(t; θ) is complete” (Voinov & Nikulin, 1996, p. 51). The concept is perhaps best understood in terms of the Lehmann-ScheffĂ© theorem…

## Prevalence in Statistics & Incidence: Simple Definition

Statistics Definitions > Prevalence in statistics Prevalence is the number of disease cases in a population; incidence is number of new cases that develop. Contents: What is Incidence in statistics? What is Prevalence in statistics? 1. Incidence Definition Incidence is…

## Kumaraswamy Distribution: Simple Definition

Probability Distributions > The Kumaraswamy distribution is a two-variable family of distributions that is bounded at one and zero. It is flexible and can be used to model a variety of shapes, and its probability density function and cumulative distribution…

## Garch Model: Simple Definition

Time Series > The GARCH model, or Generalized Autoregressive Conditionally Heteroscedastic model, was developed by doctoral student Tim Bollerslev in 1986. The goal of GARCH is to provide volatility measures for heteoscedastic time series data, much in the same way…

## Pre-Test and Post-Test Probability

RCT > Pre-test and post-test probability refers to the probability of having a disease before a diagnostic test is performed (pre-test probability) and after a test is performed (post test probability). How to Determine Pre-Test and Post-Test Probability There are…

## Residual Variance (Unexplained / Error)

Statistics Definitions > Residual Variance (also called unexplained variance or error variance) is the variance of any error (residual). The exact definition depends on what type of analysis you’re performing. For example, in regression analysis, random fluctuations cause variation around…

## Severity Distribution: Simple Definition

Probability Distribution: List of Statistical Distributions A severity distribution (or loss severity distribution) is a probability distribution of the amount of losses incurred per operational loss event. As it is a distribution (rather than a single figure or set of…