statistical sampling

简明释义

统计抽样

英英释义

例句

1.The researchers used statistical sampling to ensure that their survey accurately represented the population.

研究人员使用统计抽样来确保他们的调查准确地代表了总体。

2.The election poll was conducted using statistical sampling methods to predict voter behavior.

选举民调采用统计抽样方法来预测选民行为。

3.In quality control, statistical sampling helps identify defects in a batch of products.

在质量控制中，统计抽样有助于识别一批产品中的缺陷。

4.To evaluate customer satisfaction, the team implemented statistical sampling techniques.

为了评估客户满意度，团队实施了统计抽样技术。

5.By applying statistical sampling, the company was able to reduce costs while still obtaining reliable data.

通过应用统计抽样，公司能够降低成本，同时仍然获得可靠的数据。

作文

Statistical sampling is a fundamental technique used in research and data analysis that allows researchers to draw conclusions about a larger population based on a smaller subset of that population. This method is particularly valuable because it saves time and resources while still providing reliable insights. By utilizing statistical sampling (统计抽样), researchers can ensure that their findings are representative of the entire group, which is essential for making informed decisions.One of the primary advantages of statistical sampling (统计抽样) is its ability to reduce costs. Conducting a survey or study on an entire population can be prohibitively expensive and time-consuming. For example, if a company wants to understand customer satisfaction across its nationwide stores, surveying every customer would be impractical. Instead, by employing statistical sampling (统计抽样), the company can select a smaller group of customers that accurately reflects the demographics of its entire customer base. This not only saves money but also accelerates the data collection process.Moreover, statistical sampling (统计抽样) enhances the accuracy of research findings. When a sample is chosen correctly, it can provide insights that closely mirror those of the entire population. For instance, in political polling, organizations often use statistical sampling (统计抽样) methods to gauge public opinion. By carefully selecting a diverse group of respondents, pollsters can predict election outcomes with a high degree of confidence. This approach minimizes bias and ensures that various segments of the population are represented.However, the effectiveness of statistical sampling (统计抽样) heavily depends on how the sample is selected. Random sampling, where every member of the population has an equal chance of being chosen, is one of the most reliable methods. This technique helps eliminate selection bias, which can skew results and lead to incorrect conclusions. Conversely, non-random sampling methods, such as convenience sampling, may introduce biases that compromise the validity of the findings.In addition to random sampling, researchers often utilize stratified sampling to ensure that specific subgroups within a population are adequately represented. For example, if a researcher is studying the impact of a new educational program across different age groups, they might divide the population into strata based on age and then randomly sample from each stratum. This approach allows for a more nuanced understanding of how different segments respond to the program, thereby enriching the overall analysis.Despite its many benefits, statistical sampling (统计抽样) is not without its challenges. One significant issue is the potential for sampling error, which occurs when the sample does not perfectly represent the population. This can happen due to various factors, including a small sample size or improper sampling techniques. Researchers must be aware of these limitations and, when necessary, adjust their methodologies to mitigate the impact of sampling error.In conclusion, statistical sampling (统计抽样) is a vital tool in the field of research and data analysis. Its ability to provide reliable insights while conserving resources makes it indispensable for researchers across various disciplines. By understanding the principles and methodologies behind statistical sampling (统计抽样), researchers can enhance the quality and accuracy of their studies, ultimately leading to better decision-making and a deeper understanding of the world around us.