overall sampling

简明释义

全面抽样

英英释义

例句

1.We decided on an overall sampling 总体抽样 approach to minimize biases in our research.

我们决定采用总体抽样 总体抽样方法，以最小化研究中的偏差。

2.The research team conducted an overall sampling 总体抽样 of the population to ensure diverse representation.

研究团队对人口进行了总体抽样 总体抽样，以确保多样化的代表性。

3.For accurate results, the overall sampling 总体抽样 included both urban and rural areas.

为了获得准确的结果，总体抽样 总体抽样包括了城市和乡村地区。

4.In our survey, we used overall sampling 总体抽样 to gather data from various demographics.

在我们的调查中，我们使用了总体抽样 总体抽样来收集来自不同人群的数据。

5.The overall sampling 总体抽样 method helped us identify trends across the entire dataset.

这种总体抽样 总体抽样方法帮助我们识别了整个数据集中趋势。

作文

In the field of research and data analysis, the concept of overall sampling plays a crucial role in ensuring that the results obtained are representative of the larger population. Overall sampling refers to the process of selecting a sample that accurately reflects the characteristics of the entire population under study. This method is essential in various disciplines, including social sciences, market research, and health studies, as it helps researchers draw valid conclusions from their findings.To better understand the significance of overall sampling, consider a scenario where a researcher aims to study the dietary habits of teenagers in a particular city. If the researcher only surveys a small group of teenagers from one neighborhood, the results may not accurately represent the dietary habits of all teenagers in the city. However, by employing overall sampling, the researcher can ensure that the sample includes teenagers from diverse neighborhoods, socioeconomic backgrounds, and cultural influences. This comprehensive approach enhances the reliability of the research findings.One common technique used in overall sampling is stratified sampling. In this method, the population is divided into distinct subgroups or strata based on specific characteristics, such as age, gender, or income level. Researchers then randomly select samples from each stratum, ensuring that all segments of the population are represented. This approach minimizes bias and increases the likelihood that the sample will reflect the diversity of the population.Another important aspect of overall sampling is determining the appropriate sample size. A larger sample size generally leads to more accurate and reliable results; however, it also requires more resources and time. Researchers must strike a balance between obtaining a sufficiently large sample and managing practical constraints. Statistical formulas can assist in calculating the ideal sample size needed to achieve a desired level of confidence and precision in the results.Furthermore, overall sampling can be influenced by factors such as nonresponse bias, where certain individuals selected for the sample do not participate in the study. To mitigate this issue, researchers can implement strategies like follow-up surveys or offering incentives to encourage participation. Ensuring a high response rate is critical for maintaining the integrity of the overall sampling process.In conclusion, overall sampling is a fundamental concept in research that enables scholars and analysts to obtain accurate and representative data from a population. By employing techniques such as stratified sampling and carefully considering sample size and response rates, researchers can enhance the validity of their studies. Ultimately, the effectiveness of overall sampling directly impacts the quality of research findings, making it an essential component of the scientific method. As we continue to explore various fields of study, understanding and applying overall sampling will remain vital for producing meaningful insights that contribute to our knowledge base.

在研究和数据分析领域，整体抽样的概念在确保获得的结果能够代表更大的人群方面起着至关重要的作用。整体抽样是指选择一个样本，该样本准确反映所研究的整个群体的特征。这种方法在各种学科中都是必不可少的，包括社会科学、市场研究和健康研究，因为它帮助研究人员从他们的发现中得出有效的结论。为了更好地理解整体抽样的重要性，考虑一个场景：一位研究者希望研究某个城市青少年的饮食习惯。如果研究者只调查一个社区的小部分青少年，那么结果可能无法准确代表该城市所有青少年的饮食习惯。然而，通过采用整体抽样，研究者可以确保样本包括来自不同社区、社会经济背景和文化影响的青少年。这种全面的方法增强了研究结果的可靠性。在整体抽样中使用的一种常见技术是分层抽样。在这种方法中，人口根据特定特征（如年龄、性别或收入水平）被划分为不同的子组或层。研究人员然后从每个层中随机选择样本，确保所有人群的各个部分都得到代表。这种方法最小化了偏差，并增加了样本反映人口多样性的可能性。整体抽样的另一个重要方面是确定适当的样本大小。较大的样本大小通常会导致更准确和可靠的结果；然而，它也需要更多的资源和时间。研究人员必须在获得足够大的样本和管理实际限制之间找到平衡。统计公式可以帮助计算达到所需置信度和精确度水平所需的理想样本大小。此外，整体抽样可能会受到非响应偏差等因素的影响，即某些被选中参与样本的个体未参与研究。为了减轻这个问题，研究人员可以实施一些策略，例如后续调查或提供激励措施以鼓励参与。确保高响应率对于维护整体抽样过程的完整性至关重要。总之，整体抽样是研究中的一个基本概念，使学者和分析师能够从人群中获得准确和具有代表性的数据。通过采用如分层抽样等技术，并仔细考虑样本大小和响应率，研究人员可以提高其研究的有效性。最终，整体抽样的有效性直接影响研究结果的质量，使其成为科学方法的重要组成部分。随着我们继续探索各个研究领域，理解和应用整体抽样将仍然是产生有意义的见解的关键，这些见解将丰富我们的知识基础。