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In probability theory and statistics, the continuous uniform distributions or rectangular distributions are a family of symmetric probability distributions. Such a distribution describes an experiment where there is an arbitrary outcome that lies between certain bounds. [1] .
The uniform distribution is a continuous probability distribution and is concerned with events that are equally likely to occur. When working out problems that have a uniform distribution, be careful to note if the data is inclusive or exclusive.
For the class of continuous random variables, we will study the (continuous) Uniform Random Variable, the Exponential Random Variable, and the Normal Random Variable. We first begin with the (continuous) Uniform Random Variable.
The uniform distribution assigns equal probabilities to intervals of equal lengths, since it is a constant function, on the interval it is non-zero \([a, b]\). This is the continuous analog to equally likely outcomes in the discrete setting.
Continuous Probability Distributions - Uniform Distribution. A real-valued continuous random variable X X is uniformly distributed if the probability that X X lands in an interval is proportional to the length of that interval.
Uniform distribution. by Marco Taboga, PhD. A continuous random variable has a uniform distribution if all the values belonging to its support have the same probability density.
Continuous uniform distribution. A continuous uniform distribution is a type of symmetric probability distribution that describes an experiment in which the outcomes of the random variable have equally likely probabilities of occurring within an interval [a, b].