petit average

简明释义

港务)杂费(如引航费

英英释义

例句

1.The petit average (小平均数) is particularly useful when dealing with small datasets.

在处理小型数据集时，petit average（小平均数）特别有用。

2.During the meeting, we discussed how the petit average (小平均数) could impact our sales forecasts.

在会议上，我们讨论了petit average（小平均数）如何影响我们的销售预测。

3.In our project, we decided to use the petit average (小平均数) to find the mean value of our survey responses.

在我们的项目中，我们决定使用petit average（小平均数）来找出调查反馈的平均值。

4.The teacher explained how to calculate the petit average (小平均数) of the students' test scores.

老师解释了如何计算学生考试成绩的petit average（小平均数）。

5.To better understand the data, we calculated the petit average (小平均数) of the monthly expenses.

为了更好地理解数据，我们计算了每月开支的petit average（小平均数）。

作文

In today's fast-paced world, the concept of averages plays a crucial role in various fields such as economics, statistics, and everyday decision-making. One lesser-known term that can significantly impact our understanding of averages is petit average, which translates to 'small average' in English. This term refers to a specific type of average that focuses on a smaller subset of data rather than the entire dataset, allowing for more nuanced insights into trends and patterns. Understanding petit average can enhance our analytical skills and improve our ability to interpret data accurately.To illustrate the importance of petit average, let's consider a simple example from the realm of education. Imagine a teacher who wants to evaluate the performance of her students in a mathematics class. Instead of looking at the overall average score of the entire class, she might choose to calculate the petit average for different groups of students, such as those who struggle with certain topics or those who excel. By analyzing these smaller averages, she can identify specific areas where some students may need additional support, thereby tailoring her teaching approach to better meet their needs.Furthermore, the concept of petit average can also be applied in business settings. For instance, a company may analyze customer satisfaction ratings by segmenting them into different demographics, such as age or location. By calculating the petit average for each demographic group, the company can gain valuable insights into how different segments perceive their products or services. This targeted analysis allows businesses to make informed decisions about marketing strategies and product development, ultimately leading to improved customer satisfaction and loyalty.In the realm of data science, the use of petit average is particularly relevant when dealing with large datasets. Data scientists often encounter situations where the overall average may not provide a clear picture of the underlying trends. By focusing on petit average, they can uncover hidden patterns that would otherwise remain obscured. For example, in analyzing user behavior on a website, a data scientist might calculate the petit average of time spent on specific pages by different user groups. This information can help optimize the website's design and content to cater to the preferences of various users.Moreover, the application of petit average extends beyond academic and business contexts. In our daily lives, we often make decisions based on averages without considering the context. For instance, when choosing a restaurant, we might look at the average rating, but this does not account for individual preferences or dietary restrictions. By thinking in terms of petit average, we can refine our choices based on what appeals to our specific tastes, leading to more satisfying experiences.In conclusion, the concept of petit average offers a powerful tool for analysis and decision-making across various domains. By shifting our focus from broad averages to smaller, more specific averages, we can gain deeper insights and make more informed choices. Whether in education, business, data science, or everyday life, understanding and applying petit average can lead to enhanced outcomes and a better grasp of the complexities inherent in data interpretation. As we continue to navigate an increasingly data-driven world, embracing the nuances of averages will undoubtedly serve us well.

在当今快节奏的世界中，平均数的概念在经济学、统计学和日常决策等多个领域中发挥着至关重要的作用。一个鲜为人知的术语——petit average，即“较小的平均数”，可以显著影响我们对平均数的理解。这个术语指的是一种特定类型的平均数，它关注数据的较小子集，而不是整个数据集，从而允许我们更细致地洞察趋势和模式。理解petit average可以增强我们的分析能力，提高我们准确解读数据的能力。为了说明petit average的重要性，让我们考虑一个来自教育领域的简单例子。想象一下，一位老师想要评估她数学课堂上学生的表现。她可能不会看整个班级的平均分，而是选择计算不同学生群体的petit average，例如那些在某些主题上挣扎的学生或那些表现出色的学生。通过分析这些较小的平均数，她可以识别出一些学生可能需要额外支持的具体领域，从而调整她的教学方法，以更好地满足他们的需求。此外，petit average的概念也可以应用于商业环境。例如，一家公司可能会通过将客户满意度评分按不同的人口统计进行细分来进行分析。通过计算每个细分群体的petit average，公司可以获得有关不同细分市场如何看待其产品或服务的宝贵见解。这种针对性的分析使企业能够就市场营销策略和产品开发做出明智的决策，最终提高客户满意度和忠诚度。在数据科学领域，使用petit average在处理大数据集时尤为相关。数据科学家经常遇到整体平均数无法清晰呈现潜在趋势的情况。通过专注于petit average，他们可以发现隐藏的模式，这些模式否则可能会被掩盖。例如，在分析网站上的用户行为时，数据科学家可能会计算不同用户群体在特定页面上花费的时间的petit average。这些信息可以帮助优化网站的设计和内容，以迎合各种用户的偏好。此外，petit average的应用超越了学术和商业背景。在我们的日常生活中，我们经常基于平均数做出决策，而不考虑上下文。例如，在选择餐厅时，我们可能会查看平均评分，但这并没有考虑个人偏好或饮食限制。通过从petit average的角度思考，我们可以根据特定的口味细化我们的选择，从而带来更令人满意的体验。总之，petit average的概念为各个领域的分析和决策提供了一种强大的工具。通过将注意力从广泛的平均数转向较小、更具体的平均数，我们可以获得更深入的见解，并做出更明智的选择。无论是在教育、商业、数据科学还是日常生活中，理解和应用petit average都能带来更好的结果，并更好地掌握数据解释中的复杂性。随着我们继续在一个日益数据驱动的世界中航行，接受平均数的细微差别无疑会让我们受益匪浅。