ungrouped frequency series

简明释义

未分组频数数列

英英释义

例句

1.In statistics, an ungrouped frequency series is often used to display raw data without any categorization.

在统计学中，未分组频数系列 通常用于显示未经任何分类的原始数据。

2.For the science project, we compiled our findings into an ungrouped frequency series to make it easier to read.

为了科学项目，我们将发现汇编成一个未分组频数系列，以便于阅读。

3.When analyzing survey results, I created an ungrouped frequency series to show the exact number of responses for each option.

在分析调查结果时，我创建了一个未分组频数系列，以显示每个选项的确切响应数量。

4.The teacher asked us to convert the data into an ungrouped frequency series before starting our analysis.

老师要求我们在开始分析之前将数据转换为未分组频数系列。

5.An ungrouped frequency series can help identify patterns in small datasets quickly.

在小型数据集中，未分组频数系列 可以帮助快速识别模式。

作文

In the field of statistics, data analysis plays a crucial role in understanding patterns and trends. One of the fundamental concepts in statistics is the organization of data into various formats to facilitate analysis. Among these formats, the term ungrouped frequency series refers to a way of presenting raw data without any grouping or categorization. This method is particularly useful when dealing with small datasets, as it allows for a straightforward representation of frequencies associated with individual data points. To illustrate the concept of an ungrouped frequency series, consider a simple example where we have recorded the ages of ten individuals: 22, 25, 22, 30, 28, 25, 22, 30, 30, and 28. To create an ungrouped frequency series, we would first list each unique age along with its corresponding frequency count. In this case, the ages and their frequencies would be presented as follows: - Age 22: 3 occurrences - Age 25: 2 occurrences - Age 28: 2 occurrences - Age 30: 3 occurrences This representation provides a clear view of how many times each age appears in the dataset, making it easy to identify the most common ages among the individuals surveyed. The ungrouped frequency series is advantageous because it retains all original data points, allowing for a comprehensive understanding of the dataset’s characteristics. However, as datasets grow larger and more complex, the ungrouped frequency series may become less practical. In such cases, statisticians often resort to grouped frequency series, where data is organized into intervals or categories. This approach simplifies data presentation but may obscure some details about individual data points. Nonetheless, the ungrouped frequency series remains an essential tool for initial data exploration, providing insights that can be lost in more aggregated forms of data representation. Furthermore, the ungrouped frequency series serves as a foundational building block for more advanced statistical analysis. By understanding how to construct and interpret an ungrouped frequency series, individuals can develop a solid grasp of basic statistical principles. This knowledge is invaluable for anyone pursuing studies in fields such as mathematics, economics, psychology, or any discipline that relies on data analysis. In conclusion, the concept of an ungrouped frequency series is integral to the study of statistics. It allows researchers to present raw data clearly and concisely, facilitating the identification of patterns and trends within small datasets. While it may not be suitable for larger datasets, its simplicity and clarity make it an indispensable tool in the statistician's toolkit. Understanding and mastering the ungrouped frequency series can empower individuals to analyze data effectively and draw meaningful conclusions from their findings.

在统计学领域，数据分析在理解模式和趋势方面发挥着至关重要的作用。统计学中的一个基本概念是将数据组织成各种格式以便于分析。在这些格式中，未分组频数系列这个术语指的是一种展示原始数据而不进行任何分组或分类的方法。当处理小型数据集时，这种方法尤其有用，因为它允许对与单个数据点相关的频率进行简单明了的表示。为了说明未分组频数系列的概念，考虑一个简单的例子，我们记录了十个人的年龄：22、25、22、30、28、25、22、30、30和28。要创建未分组频数系列，我们首先列出每个独特的年龄及其相应的频率计数。在这种情况下，年龄及其频率将如下所示：- 年龄22：出现3次- 年龄25：出现2次- 年龄28：出现2次- 年龄30：出现3次这种表示方式清晰地显示了每个年龄在数据集中出现的次数，使我们能够轻松识别被调查者中最常见的年龄。未分组频数系列的优点在于它保留了所有原始数据点，从而使我们全面了解数据集的特征。然而，随着数据集的增长和复杂性增加，未分组频数系列可能变得不那么实用。在这种情况下，统计学家通常会采用分组频数系列，将数据组织成区间或类别。这种方法简化了数据呈现，但可能会掩盖关于单个数据点的一些细节。尽管如此，未分组频数系列仍然是初步数据探索的重要工具，提供了在更聚合的数据表示形式中可能丢失的洞察。此外，未分组频数系列还作为更高级统计分析的基础构建块。通过理解如何构建和解释未分组频数系列，个人可以对基本统计原理形成扎实的掌握。这一知识对于任何追求数学、经济学、心理学或任何依赖数据分析的学科的研究者来说都是无价的。总之，未分组频数系列的概念在统计学研究中是不可或缺的。它允许研究人员以清晰简洁的方式呈现原始数据，促进识别小型数据集中的模式和趋势。虽然它可能不适用于较大的数据集，但其简洁性和清晰性使其成为统计学家工具箱中不可或缺的工具。理解和掌握未分组频数系列能够赋予个人有效分析数据的能力，并从他们的发现中得出有意义的结论。