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相关概念视频

Probability Histograms01:17

Probability Histograms

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A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
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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...
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Probability Distributions01:32

Probability Distributions

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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.
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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Sampling Distribution01:12

Sampling Distribution

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Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
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Uniform Distribution01:19

Uniform Distribution

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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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Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

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The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
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窗口可观测值用于基准测量Parton分布函数

Joe Karpie1, Christopher J Monahan2, Kostas Orginos1,3

  • 1Thomas Jefferson National Accelerator Facility, Newport News, Virginia 23606, USA.

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|November 21, 2025
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概括
此摘要是机器生成的。

新的"窗口可观测值"增强了实验数据和格子量子色态动力学 (QCD) 计算之间的交叉验证,用于哈德龙结构研究. 这通过专注于可靠的动力学区域来组合数据集来提高精度.

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科学领域:

  • 高能物理 高能物理
  • 量子色态动力学 量子色态动力学
  • 子结构 子结构

背景情况:

  • 全球分析将碰撞机和固定目标数据与格子QCD计算相结合.
  • 目前的方法在动力学区域和对部分分布的推断方面存在局限性.
  • 不同方法之间的交叉验证对于准确的子结构研究至关重要.

研究的目的:

  • 为准确的交叉验证提出新的"窗口可观察值".
  • 为了使实验和格子QCD数据集更可靠地结合起来.
  • 为了克服当前全球分析动力学区域和格子QCD计算的局限性.

主要方法:

  • 开发了两个新的"窗口可观测器".
  • 在Bjorken-x.可靠的动力学区域内的可观测的定义.
  • 使用实验数据的全球分析和格子QCD计算.

主要成果:

  • 窗口可观测值允许更高精度的交叉验证.
  • 可观测值定义在全球分析和格子QCD可靠的区域.
  • 建议的可观测值保持了两种方法的灵敏度和精度.

结论:

  • 窗口可观测量为子结构研究提供了关键的进步.
  • 这些可观测因素有助于更准确地整合各种数据集.
  • 该研究提供了一条途径,通过验证的方法来改善对子结构的理解.