average sampling

简明释义

进口货指定检查

英英释义

例句

1.The researchers conducted an average sampling 平均抽样 of the population to ensure their results were representative.

研究人员对该人群进行了平均抽样 平均抽样，以确保他们的结果具有代表性。

2.The company implemented average sampling 平均抽样 to evaluate customer satisfaction across different regions.

公司实施了平均抽样 平均抽样以评估不同地区的客户满意度。

3.The survey used average sampling 平均抽样 to gather data from various demographic groups.

这项调查使用了平均抽样 平均抽样来收集来自不同人口群体的数据。

4.In quality control, average sampling 平均抽样 helps in assessing the overall quality of a batch of products.

在质量控制中，平均抽样 平均抽样 有助于评估一批产品的整体质量。

5.By applying average sampling 平均抽样, the team was able to minimize bias in their study.

通过应用平均抽样 平均抽样，团队能够最小化研究中的偏见。

作文

In the field of statistics, the concept of average sampling is crucial for understanding how data can be collected and analyzed effectively. Average sampling refers to the method of selecting a representative subset of individuals or items from a larger population to estimate characteristics of the whole group. This technique is widely used in various fields such as market research, social sciences, and quality control. By focusing on a smaller, manageable portion of the entire population, researchers can draw conclusions without needing to survey every single member.One of the primary benefits of average sampling is that it saves time and resources. For instance, if a company wants to understand customer satisfaction, they may not have the capacity to survey all their customers. Instead, they can use average sampling to select a diverse group of customers that reflects the overall population. This approach allows the company to gather insights while minimizing costs and effort.Moreover, average sampling helps to reduce bias in data collection. When done correctly, it ensures that every segment of the population has an equal chance of being included in the sample. This randomness is vital because it enhances the validity of the results. For example, if a researcher is studying the dietary habits of teenagers, they should ensure that their sample includes individuals from different backgrounds, genders, and socioeconomic statuses. If the sample is biased, the findings may not accurately represent the broader teenage population.However, it is essential to note that average sampling is not without its challenges. One significant issue is determining the appropriate sample size. A sample that is too small may not provide reliable information, while a sample that is too large can lead to unnecessary costs and complexity. Researchers often use statistical formulas to calculate the ideal sample size based on the total population and the desired confidence level.Another challenge is ensuring that the sample is truly representative. This can be difficult if certain groups are underrepresented or overrepresented in the sample. To mitigate this risk, researchers might use stratified sampling techniques, where the population is divided into subgroups, and samples are taken from each subgroup proportionally.In conclusion, average sampling is a fundamental technique in statistics that provides valuable insights while conserving resources. It plays a pivotal role in various research fields by allowing researchers to make informed decisions based on a smaller subset of data. However, careful consideration must be given to the sampling method and size to ensure that the results are valid and applicable to the larger population. As we continue to navigate an increasingly data-driven world, mastering the principles of average sampling will remain essential for researchers and decision-makers alike.

在统计学领域，平均抽样的概念对于理解如何有效地收集和分析数据至关重要。平均抽样是指从较大群体中选择一个代表性子集的方法，以估计整个群体的特征。这种技术广泛应用于市场研究、社会科学和质量控制等各个领域。通过关注整个群体中较小、可管理的部分，研究人员可以得出结论，而无需对每个成员进行调查。平均抽样的主要好处之一是节省时间和资源。例如，如果一家公司想要了解客户满意度，他们可能没有能力调查所有客户。相反，他们可以使用平均抽样选择一个多样化的客户群体，以反映整体人口。这种方法使公司能够在最小化成本和努力的同时收集见解。此外，平均抽样有助于减少数据收集中的偏差。如果操作得当，它确保每个群体的每个部分都有平等的机会被纳入样本。这种随机性至关重要，因为它增强了结果的有效性。例如，如果研究人员正在研究青少年的饮食习惯，他们应该确保样本包括来自不同背景、性别和社会经济状态的个体。如果样本存在偏差，发现的结果可能无法准确代表更广泛的青少年群体。然而，值得注意的是，平均抽样并非没有挑战。一个重要的问题是确定适当的样本大小。样本过小可能无法提供可靠的信息，而样本过大则可能导致不必要的成本和复杂性。研究人员通常使用统计公式，根据总人口和所需的置信水平来计算理想的样本大小。另一个挑战是确保样本真正具有代表性。如果某些群体在样本中被低估或高估，这可能是困难的。为了降低这种风险，研究人员可能会使用分层抽样技术，将总体划分为子组，并按比例从每个子组中抽取样本。总之，平均抽样是统计学中的一种基本技术，它在节约资源的同时提供了宝贵的见解。它在各个研究领域发挥着关键作用，使研究人员能够根据较小的数据子集做出明智的决策。然而，必须仔细考虑抽样方法和大小，以确保结果有效且适用于更大的人群。随着我们继续在日益数据驱动的世界中航行，掌握平均抽样的原则仍将对研究人员和决策者至关重要。