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相关概念视频

Probability Distributions01:32

Probability Distributions

6.8K
 The probability of a random variable x  is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson...
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Poisson Probability Distribution01:09

Poisson Probability Distribution

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A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
The...
7.8K
Expected Value01:15

Expected Value

3.8K
The expected value is known as the "long-term" average or mean. This means that over the long term of experimenting over and over, you would expect this average. The expected average is represented by the symbol μ. It is calculated as follows:
3.8K
Convolution: Math, Graphics, and Discrete Signals01:24

Convolution: Math, Graphics, and Discrete Signals

234
In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
234
Binomial Probability Distribution01:15

Binomial Probability Distribution

10.2K
A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
10.2K
Uniform Distribution01:19

Uniform Distribution

4.8K
The uniform distribution is a continuous probability distribution of events with an equal probability of occurrence. This distribution is rectangular.
Two essential properties of this distribution are
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相关实验视频

Updated: Jun 11, 2025

Observation and Analysis of Blinking Surface-enhanced Raman Scattering
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Observation and Analysis of Blinking Surface-enhanced Raman Scattering

Published on: January 11, 2018

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对离散分布的线性有条件预期.

Thaddeus Tarpey1, Richard D Sanders2

  • 1Department of Mathematics and Statistics, Wright State University, Dayton, OH, USA.

Journal of applied statistics
|October 7, 2024
PubMed
概括
此摘要是机器生成的。

离散的多变量分布经常表现出线性条件期望,这一发现得到了模拟的支持. 这项研究澄清了连续和离散数据分析的统计假设.

关键词:
条件期望是一种有条件的期望.双序列/多序列的相关性圆分布的圆分布多色的相关性,多色的相关性四合体相关性四合体相关性

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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

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Measuring Delay Discounting in Humans Using an Adjusting Amount Task
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Measuring Delay Discounting in Humans Using an Adjusting Amount Task

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相关实验视频

Last Updated: Jun 11, 2025

Observation and Analysis of Blinking Surface-enhanced Raman Scattering
05:52

Observation and Analysis of Blinking Surface-enhanced Raman Scattering

Published on: January 11, 2018

7.4K
Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

Published on: September 26, 2016

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Measuring Delay Discounting in Humans Using an Adjusting Amount Task
07:47

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Published on: January 9, 2016

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科学领域:

  • 统计 统计 统计 统计
  • 可能性理论概率理论.
  • 计量经济学 计量经济学

背景情况:

  • 许多连续数据的统计模型假定线性条件期望.
  • 多变量数据组件经常使用离散的顺序尺度来测量,这些尺度来自底层的连续潜变量.
  • 了解这些离散分布的属性对于准确的统计推理至关重要.

研究的目的:

  • 调查常见的离散多变量分布是否保持线性有条件预期.
  • 为这些分布的行为提供理论结果和经验证据.
  • 根据统计方法对混合连续和离散组件的数据的应用提供信息.

主要方法:

  • 对于离散的双变量和三变量分布的理论性质的导出.
  • 进行模拟研究以经验验证发现.
  • 在离谱化下分析条件期望.

主要成果:

  • 离散的二变和三变分布的常见例子表明了线性有条件的预期.
  • 理论结果得到模拟结果的支持.
  • 这些发现适用于潜在连续变量的典型离散方法.

结论:

  • 线性条件期望的假设通常保留在常见的离散多变量分布中.
  • 这项研究验证了在某些离散数据环境中假定线性条件期望的方法的使用.
  • 为使用顺序或离散数据进行更强大的统计建模提供了基础.