average sample

简明释义

平均试样

英英释义

例句

1.The research team collected an average sample 平均样本 from the population to analyze the data.

研究团队从人群中收集了一个平均样本 average sample以分析数据。

2.By analyzing the average sample 平均样本, we can identify trends within the data.

通过分析平均样本 average sample，我们可以识别数据中的趋势。

3.To ensure accuracy, we need to take an average sample 平均样本 of at least 100 participants.

为了确保准确性，我们需要至少抽取100名参与者的平均样本 average sample。

4.The average sample 平均样本 size in this study was significantly larger than in previous studies.

本研究中的平均样本 average sample规模显著大于之前的研究。

5.The quality control department checks the average sample 平均样本 to maintain product standards.

质量控制部门检查平均样本 average sample以维持产品标准。

作文

In the field of statistics, the concept of an average sample is crucial for understanding data trends and making informed decisions. An average sample refers to a subset of data that represents the overall population from which it is drawn. It is calculated by taking the mean of the values within that sample, providing a single value that summarizes the central tendency of the data. This is particularly useful in various domains such as psychology, market research, and healthcare, where researchers often need to draw conclusions based on limited data. For instance, consider a scenario where a company wants to understand customer satisfaction regarding a new product. Instead of surveying every single customer, which can be time-consuming and costly, the company can select an average sample of customers to gather insights. By analyzing this smaller group, the company can infer general satisfaction levels and make necessary adjustments to improve their product. This process highlights the importance of selecting a representative average sample, as biases in sampling can lead to inaccurate conclusions.Moreover, the reliability of an average sample is heavily dependent on its size and the method used for selection. A larger sample size typically yields more reliable results, as it is less likely to be influenced by outliers or anomalies. Random sampling techniques can also enhance the validity of the average sample by ensuring that every member of the population has an equal chance of being selected. This minimizes bias and allows for a more accurate representation of the population's characteristics.In addition, the concept of an average sample extends beyond numerical data. For example, in qualitative research, researchers might analyze interviews or open-ended survey responses to identify common themes or sentiments among participants. By summarizing these findings, they can present an average sample of opinions that reflects the broader perspective of the group studied.Understanding the significance of an average sample is essential for anyone involved in data analysis. It serves as a foundation for hypothesis testing, where researchers can determine if their findings from the average sample can be generalized to the entire population. This step is critical in establishing the validity of research conclusions and ensuring that decisions made based on these analyses are sound.In conclusion, an average sample plays a pivotal role in statistical analysis and research methodologies. It provides a simplified view of complex data, allowing researchers and decision-makers to derive meaningful insights without needing to examine every individual case. By carefully selecting and analyzing an average sample, one can effectively gauge the characteristics of a larger population, leading to better-informed decisions and strategies. As we continue to navigate a data-driven world, the ability to understand and utilize average samples will remain a valuable skill in various fields.

在统计学领域，平均样本的概念对于理解数据趋势和做出明智决策至关重要。平均样本是指从中提取的总体的一个子集。它通过计算该样本内数值的均值来得出，提供一个总结数据中心趋势的单一值。这在心理学、市场研究和医疗保健等多个领域尤为有用，因为研究人员通常需要根据有限的数据得出结论。例如，考虑一个公司希望了解客户对新产品的满意度的情境。与其调查每一位客户，这可能既耗时又昂贵，公司可以选择一个平均样本的客户来收集见解。通过分析这个较小的群体，公司可以推断出一般的满意度水平，并做出必要的调整以改善他们的产品。这个过程突显了选择代表性平均样本的重要性，因为抽样中的偏差可能导致不准确的结论。此外，平均样本的可靠性在很大程度上依赖于其大小和选择方法。较大的样本量通常会产生更可靠的结果，因为它不太可能受到离群值或异常值的影响。随机抽样技术也可以通过确保总体中的每个成员都有相等的被选中机会来增强平均样本的有效性。这最小化了偏差，使得对总体特征的更准确的表示成为可能。此外，平均样本的概念超越了数值数据。例如，在定性研究中，研究人员可能会分析访谈或开放式调查响应，以识别参与者之间的共同主题或情感。通过总结这些发现，他们可以呈现一个反映所研究群体更广泛观点的平均样本。理解平均样本的重要性对于任何参与数据分析的人来说都是必不可少的。它作为假设检验的基础，研究人员可以确定他们从平均样本中获得的发现是否可以推广到整个总体。这一步对建立研究结论的有效性至关重要，确保基于这些分析做出的决策是合理的。总之，平均样本在统计分析和研究方法中扮演着关键角色。它提供了一种简化复杂数据的视角，使研究人员和决策者能够在不需要检查每个个案的情况下得出有意义的见解。通过仔细选择和分析平均样本，人们可以有效地评估更大群体的特征，从而导致更为明智的决策和策略。随着我们继续在数据驱动的世界中航行，理解和利用平均样本的能力将在各个领域保持一种宝贵的技能。