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→Basic terms 基本术语
* '''Tail''':<ref name='tail'>More information and examples can be found in the articles [[Heavy-tailed distribution]], [[Long-tailed distribution]], [[fat-tailed distribution]]</ref> the regions close to the bounds of the random variable, if the pmf or pdf are relatively low therein. Usually has the form <math>X > a</math>, <math>X < b</math> or a union thereof.
* '''Tail''':<ref name='tail'>More information and examples can be found in the articles [[Heavy-tailed distribution]], [[Long-tailed distribution]], [[fat-tailed distribution]]</ref> the regions close to the bounds of the random variable, if the pmf or pdf are relatively low therein. Usually has the form <math>X > a</math>, <math>X < b</math> or a union thereof.
尾巴：如果pmf或pdf相对较低，则靠近随机变量边界的区域。通常形式为X> a，X <b或它们的并集。
尾巴：如果pmf或pdf相对较低，则靠近随机变量边界的区域。通常形式为X> a，X <b或它们的并集。
--[[用户:普天星相|普天星相]]([[用户讨论:普天星相|讨论]]) 【审校】此句前一半改为“尾部：当pmf或pdf相对较低时，靠近随机变量边界的区域。”
*'''Head''':<ref name='tail' /> the region where the pmf or pdf is relatively high. Usually has the form <math>a < X < b</math>.
*'''Head''':<ref name='tail' /> the region where the pmf or pdf is relatively high. Usually has the form <math>a < X < b</math>.
* '''[[Expected value]]''' or '''mean''': the [[weighted average]] of the possible values, using their probabilities as their weights; or the continuous analog thereof.
* '''[[Expected value]]''' or '''mean''': the [[weighted average]] of the possible values, using their probabilities as their weights; or the continuous analog thereof.
期望值或均值：可能值的加权平均值，以其概率作为权重；或其连续类似物。
期望值或均值：可能值的加权平均值，以其概率作为权重；或其连续类似物。
--[[用户:普天星相|普天星相]]([[用户讨论:普天星相|讨论]]) 【审校】此句“或其连续类似物”改为“或连续随机变量的类似取值。”
A continuous probability distribution is a probability distribution whose support is an uncountable set, such as an interval in the real line. They are uniquely characterized by a cumulative density function that can be used to calculate the probability for each subset of the support. There are many examples of continuous probability distributions: normal, uniform, chi-squared, and others.
A continuous probability distribution is a probability distribution whose support is an uncountable set, such as an interval in the real line. They are uniquely characterized by a cumulative density function that can be used to calculate the probability for each subset of the support. There are many examples of continuous probability distributions: normal, uniform, chi-squared, and others.