uniformly distributed

简明释义

均匀分布负荷

英英释义

例句

1.In a random sample, the data points were found to be uniformly distributed 均匀分布 across the entire range.

在随机样本中，数据点被发现均匀分布在整个范围内。

2.The particles in the gas are assumed to be uniformly distributed 均匀分布 throughout the container.

假设气体中的粒子在容器中是均匀分布的。

3.When rolling a fair die, the outcomes are uniformly distributed 均匀分布 between 1 and 6.

掷一个公平的骰子时，结果在1到6之间是均匀分布的。

4.The lottery numbers are uniformly distributed 均匀分布 to ensure fairness.

彩票号码是均匀分布的，以确保公平性。

5.In this experiment, we need to ensure that the samples are uniformly distributed 均匀分布 to avoid bias.

在这个实验中，我们需要确保样本是均匀分布的，以避免偏差。

作文

In the realm of mathematics and statistics, the concept of randomness plays a crucial role in understanding various phenomena. One of the key terms associated with randomness is 'uniformly distributed'. When we say that a variable is uniformly distributed, we mean that every possible outcome has an equal chance of occurring. This principle is fundamental in probability theory and has numerous applications in real-world scenarios. For instance, when rolling a fair six-sided die, each number from one to six has an equal probability of 1/6. Therefore, we can say that the outcomes are uniformly distributed across the possible results.The importance of uniformly distributed variables extends beyond simple games of chance. In computer simulations, for example, random numbers are often generated to mimic real-world processes. If these numbers are uniformly distributed, it ensures that the simulation accurately reflects the randomness of the actual situation being modeled. This is particularly important in fields such as finance, where accurate modeling of risk and uncertainty can have significant implications for investment strategies.Moreover, in the context of statistical sampling, having a uniformly distributed sample is essential for drawing valid conclusions. If a researcher collects data from a population that is uniformly distributed, they can be more confident that their findings are representative of the entire population. This is crucial in areas such as public health, where policies and interventions are often based on data collected from samples.However, achieving a uniformly distributed dataset is not always straightforward. Various biases can lead to skewed distributions, where some outcomes are favored over others. For example, if a survey is conducted only among a specific demographic group, the results may not reflect the views of the broader population. Researchers must be vigilant in ensuring that their methods promote uniformly distributed outcomes to avoid misleading conclusions.In conclusion, the concept of uniformly distributed variables is a cornerstone of probability and statistics. It provides a framework for understanding randomness and its implications in various fields. From gaming to finance and public health, the principle of uniformly distributed outcomes is essential for making informed decisions based on data. As we continue to navigate an increasingly data-driven world, the significance of ensuring that our data is uniformly distributed cannot be overstated. By striving for true randomness in our analyses, we can enhance the reliability and validity of our conclusions, ultimately leading to better outcomes in both research and practice.

在数学和统计学的领域中，随机性的概念在理解各种现象中扮演着至关重要的角色。与随机性相关的一个关键术语是“均匀分布”。当我们说一个变量是均匀分布时，我们的意思是每一个可能的结果都有相等的机会发生。这个原则在概率论中是基础，并且在现实世界的场景中有许多应用。例如，当掷一个公平的六面骰子时，从一到六的每个数字都有1/6的相等概率。因此，我们可以说这些结果在可能的结果中是均匀分布的。均匀分布变量的重要性超越了简单的机会游戏。在计算机模拟中，例如，通常会生成随机数以模拟现实过程。如果这些数字是均匀分布的，它确保模拟准确反映实际情况的随机性。这在金融等领域尤为重要，因为对风险和不确定性的准确建模对投资策略有重大影响。此外，在统计抽样的背景下，拥有均匀分布的样本对于得出有效结论至关重要。如果研究人员从一个均匀分布的人群中收集数据，他们可以更有信心他们的发现代表整个群体。这在公共卫生等领域至关重要，因为政策和干预措施往往基于从样本中收集的数据。然而，获得均匀分布的数据集并不总是简单的。各种偏见可能导致分布失衡，其中一些结果被优先考虑。例如，如果一项调查仅在特定的人口群体中进行，结果可能无法反映更广泛人群的观点。研究人员必须警惕，确保他们的方法促进均匀分布的结果，以避免误导性结论。总之，均匀分布变量的概念是概率和统计的基石。它提供了理解随机性及其在各个领域影响的框架。从游戏到金融和公共卫生，均匀分布结果的原则对于根据数据做出明智决定至关重要。随着我们继续在一个日益数据驱动的世界中航行，确保我们的数据是均匀分布的重要性不容低估。通过努力实现分析中的真正随机性，我们可以增强结论的可靠性和有效性，最终在研究和实践中获得更好的结果。