chance distribution

简明释义

1. 随机分布; 2. 概率分布;

英英释义

例句

1.The chance distribution for this experiment indicates that there is a higher probability of success under certain conditions.

这个实验的chance distribution表明在某些条件下成功的概率更高。

2.Researchers often analyze the chance distribution of a sample to make predictions about a larger population.

研究人员通常分析一个样本的chance distribution以对更大的人群做出预测。

3.The chance distribution of rolling a die shows that each number has an equal likelihood of appearing.

掷骰子的chance distribution显示每个数字出现的可能性是相等的。

4.In statistics, the concept of chance distribution is essential for understanding how probabilities are spread across different outcomes.

在统计学中，chance distribution的概念对于理解概率如何在不同结果之间分布至关重要。

5.Understanding the chance distribution of customer preferences can help businesses tailor their marketing strategies.

理解客户偏好的chance distribution可以帮助企业调整其营销策略。

作文

In the realm of statistics and probability theory, understanding the concept of chance distribution is crucial for analyzing random events. A chance distribution refers to the way in which the probabilities of various outcomes are spread out or distributed in a given scenario. This concept plays a fundamental role in predicting the likelihood of different results occurring in experiments, surveys, and real-world situations.To illustrate this concept, let’s consider a simple example involving a six-sided die. When you roll the die, there are six possible outcomes: 1, 2, 3, 4, 5, or 6. Each outcome has an equal probability of occurring, specifically 1/6. The chance distribution for this scenario is uniform, meaning that each outcome is equally likely to happen. This uniform distribution is a basic example of how chance distribution can be understood in a straightforward manner.However, not all chance distributions are uniform. In many real-life situations, some outcomes may be more likely than others. For instance, if we consider the distribution of heights in a population, we might find that most people are around average height, while there are fewer individuals who are very short or very tall. This creates a bell-shaped curve known as a normal distribution. Understanding the chance distribution of heights allows researchers to make predictions about the population, such as estimating how many people fall within a certain height range.The significance of chance distribution extends beyond mere academic interest; it has practical applications in various fields. For example, in finance, investors use chance distributions to assess the risks associated with different investment options. By analyzing the potential returns and their respective probabilities, they can make informed decisions that align with their risk tolerance.Moreover, in the field of genetics, researchers utilize chance distributions to predict the likelihood of inheriting certain traits. For instance, when studying Mendelian inheritance patterns, scientists can calculate the probabilities of offspring inheriting specific characteristics based on the genetic makeup of their parents. This application of chance distribution helps in understanding heredity and the transmission of traits through generations.In conclusion, the concept of chance distribution is a foundational element in the study of probability and statistics. It provides a framework for understanding how different outcomes are likely to occur in various scenarios. Whether examining the roll of a die, analyzing population characteristics, making financial decisions, or studying genetics, the principles of chance distribution guide our understanding of randomness and uncertainty. As we continue to explore the complexities of data and probability, mastering the concept of chance distribution will undoubtedly enhance our ability to make informed decisions in both academic and real-world contexts.

在统计学和概率论的领域中，理解机会分布的概念对于分析随机事件至关重要。机会分布指的是在特定场景中，各种结果的概率是如何分布或扩散的。这个概念在预测实验、调查和现实世界情境中不同结果发生的可能性方面发挥着基础作用。为了说明这一概念，让我们考虑一个简单的例子，涉及到一个六面骰子。当你掷骰子时，有六种可能的结果：1、2、3、4、5或6。每个结果发生的概率都是相等的，具体为1/6。这个场景的机会分布是均匀的，意味着每个结果发生的可能性是相同的。这种均匀分布是如何在简单的方式下理解机会分布的基本示例。然而，并非所有的机会分布都是均匀的。在许多现实生活中的情境中，某些结果可能比其他结果更可能发生。例如，如果我们考虑一个人口的身高分布，我们可能会发现大多数人的身高接近平均水平，而非常矮或非常高的人则相对较少。这就形成了一个钟形曲线，称为正态分布。理解身高的机会分布使研究人员能够对该人群进行预测，例如估计有多少人落在某个身高范围内。机会分布的重要性超越了单纯的学术兴趣；它在各个领域都有实际应用。例如，在金融领域，投资者利用机会分布来评估与不同投资选项相关的风险。通过分析潜在回报及其各自的概率，他们可以做出与自身风险承受能力相符的明智决策。此外，在遗传学领域，研究人员利用机会分布来预测遗传某些特征的可能性。例如，在研究孟德尔遗传模式时，科学家可以根据父母的遗传构成计算后代继承特定特征的概率。这个机会分布的应用有助于理解遗传和特征在几代人之间的传播。总之，机会分布的概念是概率和统计研究中的基础元素。它提供了一个框架，用于理解在各种情境中不同结果发生的可能性。无论是在掷骰子、分析人口特征、做出财务决策还是研究遗传学，机会分布的原则都引导着我们对随机性和不确定性的理解。随着我们继续探索数据和概率的复杂性，掌握机会分布的概念无疑将增强我们在学术和现实世界情境中做出明智决策的能力。