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词汇 Discrete Random Variable
分类 英语词汇 英语翻译词典
释义

Discrete Random Variable

原声例句
可汗学院:统计学(视频版)

You can have discrete random variables, or continuous.

你可以有离散的随机变量,也可以是连续的。

可汗学院:统计学(视频版)

While, with the discrete random variables, it just took on a finite number of values.

而对于离散随机变量,它只是取了有限数量的值。

可汗学院:统计学(视频版)

You have discrete, so finite meaning you can't have an infinite number of values for a discrete random variable.

你有离散的,所以有限意味着你不能为离散随机变量拥有无限数量的值。

可汗学院:统计学(视频版)

Well, based on how we thought about the probability distribution functions for the discrete random variable, you'd say OK, let's see.

好吧,根据我们对离散随机变量的概率分布函数的看法, 你会说好吧, 让我们看看。

可汗学院:统计学(视频版)

So it's important to realize that a probability distribution function, in this case for a discrete random variable, they all have to add up to 1.

所以重要的是要认识到概率分布函数,在这种情况下对于离散随机变量, 它们都必须加起来为 1。

英语百科

Probability distribution

The probability mass function (pmf) p(S) specifies the probability distribution for the sum S of counts from two dice.  For example, the figure shows that p(11) = 1/18.  The pmf allows the computation of probabilities of events such as P(S > 9) = 1/12 + 1/18 + 1/36 = 1/6, and all other probabilities in the distribution.
The probability density function (pdf) of the normal distribution, also called Gaussian or
The probability mass function of a discrete probability distribution. The probabilities of the singletons 1, 3, and 7 are respectively 0.2, 0.5, 0.3. A set not containing any of these points has probability zero.

In probability and statistics, a probability distribution assigns a probability to each measurable subset of the possible outcomes of a random experiment, survey, or procedure of statistical inference. Examples are found in experiments whose sample space is non-numerical, where the distribution would be a categorical distribution; experiments whose sample space is encoded by discrete random variables, where the distribution can be specified by a probability mass function; and experiments with sample spaces encoded by continuous random variables, where the distribution can be specified by a probability density function. More complex experiments, such as those involving stochastic processes defined in continuous time, may demand the use of more general probability measures.

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