small sample

简明释义

小包货样

英英释义

例句

1.The research findings were based on a small sample, which limits the generalizability of the results.

研究结果基于一个小样本，这限制了结果的普遍适用性。

2.The small sample size made it difficult to draw any significant conclusions.

这个小样本的大小使得很难得出任何显著的结论。

3.We conducted a survey using a small sample of participants to gather initial feedback.

我们使用一个小样本的参与者进行调查，以收集初步反馈。

4.In our experiment, we tested a small sample of the population to see if the drug was effective.

在我们的实验中，我们对人群进行了一个小样本的测试，以查看药物是否有效。

5.Due to time constraints, we only had a small sample to analyze for our report.

由于时间限制，我们只能分析一个小样本用于我们的报告。

作文

In the field of research, the term small sample refers to a limited number of observations or data points collected for analysis. While conducting studies, researchers often face the challenge of gathering enough data to draw meaningful conclusions. A small sample can lead to various issues, including a lack of statistical power and the potential for bias in the results. For instance, consider a clinical trial aimed at testing the effectiveness of a new medication. If the researchers only include a small sample of participants, the findings may not accurately represent the broader population. This can result in misleading conclusions about the drug's efficacy and safety. Therefore, it is crucial for researchers to ensure that their sample size is adequate to support their hypotheses. Moreover, a small sample can also affect the reliability of the results. When the sample size is too small, random variations can have a more significant impact on the outcomes. This means that the results obtained from a small sample might be due to chance rather than a true effect. To mitigate this risk, researchers often use statistical techniques to estimate the potential variability in their results. In many cases, researchers may resort to using a small sample due to constraints such as time, budget, or availability of participants. However, it is essential to acknowledge the limitations that come with a small sample. Researchers should clearly communicate these limitations in their reports and discussions, providing context for their findings. This transparency helps other scholars and practitioners understand the scope of the study and the applicability of its results. Additionally, while a small sample may hinder the generalizability of findings, it can still provide valuable insights, especially in exploratory research. In qualitative studies, for example, a small sample can allow for in-depth exploration of participants' experiences and perspectives. Such studies can uncover themes and patterns that might not emerge in larger, more quantitative research designs. In conclusion, while a small sample presents challenges in terms of reliability and generalizability, it can still offer useful information in specific contexts. Researchers must carefully consider their study design and the implications of working with a small sample. By acknowledging the limitations and being transparent about the findings, they can contribute valuable knowledge to their field, even when working with a small sample. Ultimately, the goal of research is to advance understanding, and every piece of data, regardless of sample size, plays a role in that journey.

在研究领域，术语small sample指的是收集的有限数量的观察或数据点用于分析。在进行研究时，研究人员常常面临收集足够数据以得出有意义结论的挑战。small sample可能导致各种问题，包括缺乏统计能力和结果中潜在的偏见。例如，考虑一个旨在测试新药物有效性的临床试验。如果研究者仅包含一个small sample的参与者，那么得到的发现可能无法准确代表更广泛的人群。这可能导致对药物疗效和安全性的误导性结论。因此，研究人员确保他们的样本量足够支持他们的假设是至关重要的。此外，small sample还可能影响结果的可靠性。当样本量太小的时候，随机变异对结果的影响可能会更大。这意味着从small sample中获得的结果可能是由于偶然，而不是一个真实的效应。为了减少这种风险，研究人员通常使用统计技术来估计结果的潜在变异性。在许多情况下，由于时间、预算或参与者的可用性等限制，研究人员可能不得不使用small sample。然而，承认与small sample相关的局限性是至关重要的。研究人员应在报告和讨论中清晰地传达这些局限性，为他们的发现提供背景。这种透明度帮助其他学者和从业者理解研究的范围及其结果的适用性。此外，虽然small sample可能阻碍结果的普遍适用性，但它仍然可以在特定上下文中提供有价值的见解。例如，在定性研究中，small sample可以让研究人员深入探讨参与者的经历和观点。这类研究可以揭示在更大、更量化的研究设计中可能不会出现的主题和模式。总之，虽然small sample在可靠性和普遍适用性方面带来了挑战，但在特定情况下仍然可以提供有用的信息。研究人员必须仔细考虑他们的研究设计以及与small sample相关的影响。通过承认局限性并对发现保持透明，他们可以为其领域贡献有价值的知识，即使是在处理small sample的情况下。最终，研究的目标是推动理解，而每一条数据，无论样本大小，都在这一旅程中扮演着角色。