Uniform distribution (discrete)
Talk0this wiki
Assessment |
Biopsychology |
Comparative |
Cognitive |
Developmental |
Language |
Individual differences |
Personality |
Philosophy |
Social |
Methods |
Statistics |
Clinical |
Educational |
Industrial |
Professional items |
World psychology |
Statistics: Scientific method · Research methods · Experimental design · Undergraduate statistics courses · Statistical tests · Game theory · Decision theory
Probability mass function n=5 where n=b-a+1 | |
Cumulative distribution function n=5 where n=b-a+1. The convention is used that the cumulative mass function is the probability that | |
Parameters | |
Support | |
Template:Probability distribution/link mass | |
cdf | |
Mean | |
Median | |
Mode | N/A |
Variance | |
Skewness | |
Kurtosis | |
Entropy | |
mgf | |
Char. func. |
In probability theory and statistics, the discrete uniform distribution is a discrete probability distribution that can be characterized by saying that all values of a finite set of possible values are equally probable.
A random variable that has any of possible values that are equally probable, has a discrete uniform distribution, then the probability of any outcome is . A simple example of the discrete uniform distribution is throwing a fair die. The possible values of are 1, 2, 3, 4, 5, 6; and each time the die is thrown, the probability of a given score is 1/6.
In case the values of a random variable with a discrete uniform distribution are real, it is possible to express the cumulative distribution function in terms of the degenerate distribution; thus
where the Heaviside step function is the CDF of the degenerate distribution centered at . This assumes that consistent conventions are used at the transition points.
See rencontres numbers for an account of the probability distribution of the number of fixed points of a uniformly distributed random permutation.de:Diskrete Gleichverteilungnl:Discrete uniforme verdeling fr:loi uniforme discrète
This page uses Creative Commons Licensed content from Wikipedia (view authors). |