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In probability theory, a probability density function ( PDF ), density function, or density of an absolutely continuous random variable, is a function whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a relative likelihood that the value of ...
Probability theory. In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is The parameter is the mean or expectation of the distribution (and also its median and mode ), while ...
Cumulative distribution function for the exponential distribution Cumulative distribution function for the normal distribution. In probability theory and statistics, the cumulative distribution function (CDF) of a real-valued random variable, or just distribution function of , evaluated at , is the probability that will take a value less than or equal to .
In statistics, the k th order statistic of a statistical sample is equal to its k th-smallest value. [ 1 ] Together with rank statistics, order statistics are among the most fundamental tools in non-parametric statistics and inference . Important special cases of the order statistics are the minimum and maximum value of a sample, and (with some ...
Statistics (from German: Statistik, orig. "description of a state, a country") [ 1][ 2] is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. [ 3][ 4][ 5] In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or ...
The Ewens's sampling formula is a probability distribution on the set of all partitions of an integer n, arising in population genetics. The Balding–Nichols model; The multinomial distribution, a generalization of the binomial distribution. The multivariate normal distribution, a generalization of the normal distribution.
The graph of a probability mass function. All the values of this function must be non-negative and sum up to 1. In probability and statistics, a probability mass function (sometimes called probability function or frequency function [1]) is a function that gives the probability that a discrete random variable is exactly equal to some value. [2]
In descriptive statistics, the range of a set of data is size of the narrowest interval which contains all the data. It is calculated as the difference between the largest and smallest values (also known as the sample maximum and minimum ). [ 1] It is expressed in the same units as the data. The range provides an indication of statistical ...
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