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相关概念视频

Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

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A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
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Bias

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Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
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Probability in Statistics01:14

Probability in Statistics

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Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
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Probability Distributions01:32

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 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.
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Determination of Expected Frequency01:08

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Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
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Random Variables01:09

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A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
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水平频率假设和子模拟.

Jonathan Lee Mace1, Travis B Peery1, Scott W Teare2

  • 1Weapon Systems Safety Analysis, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA.

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此摘要是机器生成的。

提出了一个关于平面频率的新假设,类似于Onsager回归假设. 这项工作使用子模型演示了能量水平之间的波动时间,为统计力学提供了洞察力.

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科学领域:

  • 统计力学 统计力学
  • 物理化学 物理化学
  • 热力学是一种热力学.

背景情况:

  • 恩萨格回归假说是理解物理系统平衡方法的一个基本概念.
  • 描述热力学状态之间的波动动态和时间尺度对于理解系统演变至关重要.
  • 模拟系统可以为复杂的粒子行为和统计分布提供宝贵的见解.

研究的目的:

  • 在Onsager回归假说的框架内提出一个水平频率假设.
  • 导出和证明能量水平之间的波动时间的概念.
  • 为了建立一个比喻,在一个子系统和孤立的复合粒子系统.

主要方法:

  • 提出了一个水平频率假设.
  • 利用红色和白色子的模拟系统来模拟能量水平波动.
  • 导出水平概率分布以建立系统类比.
  • 为水平波动时间开发了一种代数表达式.

主要成果:

  • 使用子模拟系统证明了能量水平之间的波动时间.
  • 通过概率分布建立了子系统与孤立复合粒子系统的类比.
  • 用平均能量和高斯参数代数表达水平波动时间.
  • 展示了准静态进化作为在波动时间上的积分.

结论:

  • 提出的水平频率假设有效地模拟了波动动态.
  • 子模拟系统提供了统计力学原理的切实表现.
  • 波动时间的衍生代数表达式为分析提供了定量工具.