hypergeometric

hypergeometric 的音标是[ˌhaɪpərˈdʒɜːmɪtɪk]，基本翻译是超几何学的，速记技巧是“海菊”=hypergeometric（超几何学的）。

Hypergeometric这个词来源于希腊语，意为“超越几何的”。它的变化形式包括hypergeometrician（超几何学家），hypergeometricianism（超几何学派）。相关单词有：

1. Hypergeometric series（超几何级数）：一种在数学中用于描述特定形状或分布的公式，特别是在统计和概率论中。

2. Hypergeometric distribution（超几何分布）：一种统计分布，用于从给定数量的成功和失败的独立试验中估计概率。

3. Hypergeometric probability（超几何概率）：一种特殊的概率分布，用于描述在有限样本空间中随机抽取特定样本的条件下的事件的概率。

4. Hypergeometric function（超几何函数）：一种数学函数，用于描述超几何分布的概率密度。

5. Hypergeometric distribution curve（超几何分布曲线）：一种描述超几何分布的概率密度的曲线。

这些单词都与超几何学有关，是数学和统计学中的重要概念。它们在科学研究和实际应用中发挥着重要作用。

常用短语：

1. hypergeometric distribution

2. hypergeometric probability

3. hypergeometric sample

4. hypergeometric model

5. hypergeometric distribution formula

6. hypergeometric random variable

7. hypergeometric theory

例句：

1. The hypergeometric probability of drawing a red ball from a bag containing 10 blue and 20 red balls is 70%.

2. The hypergeometric model is widely used in biological and medical research.

3. The hypergeometric distribution formula is simple and easy to use.

4. Hypergeometric random variables are commonly used in statistical analysis.

5. Hypergeometric theory is a fundamental part of mathematical statistics.

英文小作文：

Hypergeometric Theory: An Introduction

Hypergeometric theory is a fundamental part of mathematical statistics, playing a crucial role in many areas such as biological and medical research, genetic engineering, and more. It is a statistical model that assumes that the probability of an event happening depends on the relative frequency of the event in a large population of similar events.

In the hypergeometric model, a sample is drawn from a larger population, and the probability of drawing an item from the sample is determined by the relative sizes of the two populations and the number of items in the sample. This model is particularly useful for situations where the number of items in the larger population is large compared to the number of items in the smaller population, and where the items in the smaller population are relatively rare compared to the items in the larger population.

For example, imagine a farmer who has 100 apples and 20 oranges in a bag, and wants to draw a fruit from the bag to eat. The hypergeometric model can be used to determine the probability of drawing an apple or an orange, given that there are more oranges than apples in the bag, and that there are only a limited number of fruits in the bag to draw from. This model can also be extended to more complex situations where multiple items are drawn from multiple populations, allowing for more accurate predictions and analysis of complex data sets.