chance sample

简明释义

随机样品;

英英释义

例句

1.The results obtained from the chance sample were surprising and led to new hypotheses.

从随机样本获得的结果令人惊讶，并导致了新的假设。

2.In a research study, the team decided to use a chance sample to gather data from the general population.

在一项研究中，团队决定使用随机样本从普通人群中收集数据。

3.When conducting surveys, it's important to ensure that your chance sample is representative of the entire population.

进行调查时，确保你的随机样本能够代表整个群体是很重要的。

4.The marketing team selected a chance sample of customers to test the new product.

市场团队选择了一组随机样本客户来测试新产品。

5.Using a chance sample can help eliminate bias in the data collection process.

使用随机样本可以帮助消除数据收集过程中的偏见。

作文

In the field of statistics, the concept of a chance sample is fundamental to understanding how data is collected and interpreted. A chance sample refers to a subset of individuals chosen from a larger population in such a way that each individual has an equal opportunity of being selected. This method of sampling is crucial because it helps to eliminate biases that can skew results and lead to inaccurate conclusions. For example, if a researcher wants to study the eating habits of teenagers in a city, they might use a chance sample by randomly selecting teenagers from different neighborhoods rather than just surveying those from a single area. This approach ensures that the sample accurately reflects the diverse eating habits of the entire population.One of the key advantages of using a chance sample is that it enhances the validity of the research findings. When every member of the population has an equal chance of being included in the sample, the results are more likely to be representative of the whole group. This is particularly important in fields like public health, where decisions based on biased data can have significant consequences. For instance, if a health organization conducts a survey about vaccination rates but only samples individuals from affluent neighborhoods, the findings may indicate higher vaccination rates than actually exist across the broader population. Therefore, employing a chance sample can lead to more informed decision-making and better policy development.However, achieving a truly random chance sample can be challenging. Researchers must carefully design their sampling methods to avoid any form of bias that could inadvertently influence the results. This might involve using random number generators or lottery systems to select participants. Additionally, researchers need to ensure that the sample size is adequate to provide reliable results. A small chance sample may not capture the variability within a population, leading to erroneous conclusions.Moreover, while a chance sample is beneficial for obtaining unbiased data, it is not without its limitations. In some cases, certain groups within a population may be underrepresented simply due to the randomness of the selection process. For example, if a chance sample results in fewer participants from minority communities, the findings may overlook critical insights into their specific needs and challenges. Consequently, researchers may need to complement their chance sample with additional targeted sampling methods to ensure that all segments of the population are adequately represented.In conclusion, the use of a chance sample is a vital aspect of effective research methodology. It provides a mechanism for collecting data that is free from bias, thus enhancing the reliability and validity of the findings. While challenges exist in achieving a perfectly random sample, the benefits of using a chance sample far outweigh the drawbacks. By prioritizing this sampling method, researchers can contribute to a more accurate understanding of the populations they study, ultimately leading to better outcomes in various fields such as healthcare, education, and social sciences. Understanding and applying the principles of a chance sample is essential for anyone involved in research, as it lays the foundation for credible and impactful results.

在统计学领域，随机样本的概念对于理解数据的收集和解释至关重要。随机样本是指从一个较大的人群中选择的个体子集，其选择方式使每个个体都有相等的被选机会。这种抽样方法至关重要，因为它有助于消除可能扭曲结果并导致不准确结论的偏见。例如，如果研究者想要研究一个城市青少年的饮食习惯，他们可以通过从不同社区随机选择青少年来使用随机样本，而不是仅仅调查某一个地区的青少年。这种方法确保样本准确反映整个群体的多样化饮食习惯。使用随机样本的一个主要优点是增强了研究结果的有效性。当每个群体成员都有均等的机会被纳入样本时，结果更可能代表整个群体。这在公共卫生等领域尤为重要，因为基于偏见数据做出的决策可能会产生重大后果。例如，如果一家健康组织进行关于疫苗接种率的调查，但只对富裕社区的个体进行抽样，那么调查结果可能表明接种率高于实际存在的情况。因此，采用随机样本可以导致更明智的决策和更好的政策制定。然而，实现真正随机的随机样本可能具有挑战性。研究人员必须仔细设计他们的抽样方法，以避免任何可能无意中影响结果的偏见。这可能涉及使用随机数生成器或抽奖系统来选择参与者。此外，研究人员需要确保样本量足够，以提供可靠的结果。小的随机样本可能无法捕捉到人群中的变异性，从而导致错误的结论。此外，尽管随机样本在获得无偏数据方面具有优势，但它并非没有局限性。在某些情况下，由于选择过程的随机性，某些群体可能在样本中被低估。例如，如果一个随机样本导致少数群体的参与者较少，那么调查结果可能会忽视他们特定需求和挑战的关键见解。因此，研究人员可能需要补充他们的随机样本，采用额外的针对性抽样方法，以确保所有人群的各个部分得到充分代表。总之，使用随机样本是有效研究方法论的重要方面。它提供了一种收集无偏数据的机制，从而增强了研究发现的可靠性和有效性。虽然在实现完全随机样本方面存在挑战，但使用随机样本的好处远远超过缺点。通过优先考虑这种抽样方法，研究人员可以为更准确地理解他们所研究的人群做出贡献，最终在医疗保健、教育和社会科学等各个领域取得更好的成果。理解和应用随机样本的原则对任何参与研究的人来说都是至关重要的，因为它为可信和有影响力的结果奠定了基础。