Analysis of Relationships between Common Distributions Based on Computing Science
Xiaobo Wen
Abstract
Open-access reader
Xiaobo Wen
Abstract
Open-access reader
Random variables are the most fundamental concept in probability theory and mathematical statistics. Each random variable can have a distribution, different random variables can have different distributions, and different random variables can have the same distribution. There are many random variables, and there are many distributions that can be formed, but there are not many commonly used distributions. In general probability theory and mathematical statistics textbooks, each distribution is explained separately, and the relationship between distributions is occasionally discussed, and there is no detailed description. Establishing the correspondence between distributions plays an important role in mastering the theory and relationship of common distributions. This paper studies the relationship between distributions, and establishes some common distribution diagrams on the basis of distribution relationships, so as to illustrate the connections between some distributions with distribution diagrams.
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Random variables are the most fundamental concept in probability theory and mathematical statistics. Each random variable can have a distribution, different random variables can have different distributions, and different random variables can have the same distribution. There are many random variables, and there are many distributions that can be formed, but there are not many commonly used distributions. In general probability theory and mathematical statistics textbooks, each distribution is explained separately, and the relationship between distributions is occasionally discussed, and there is no detailed description. Establishing the correspondence between distributions plays an important role in mastering the theory and relationship of common distributions. This paper studies the relationship between distributions, and establishes some common distribution diagrams on the basis of distribution relationships, so as to illustrate the connections between some distributions with distribution diagrams.
Key concepts: Inverse distribution, Mathematics, Random variable, Heavy-tailed distribution, Probability distribution, Sum of normally distributed random variables, Algebra of random variables, Probability integral transform