reduction of observation

简明释义

观测订正

英英释义

例句

1.The study showed a significant reduction of observation 观察减少 time when using automated data collection methods.

研究表明，使用自动数据收集方法时，观察减少的时间显著减少。

2.The reduction of observation 观察减少 in environmental studies helps researchers focus on key variables.

在环境研究中，观察减少帮助研究人员关注关键变量。

3.Our findings indicate a reduction of observation 观察减少 error in the data collection process.

我们的发现表明，在数据收集过程中存在观察减少错误。

4.The software implemented a reduction of observation 观察减少 strategy to enhance user experience.

该软件实施了一个观察减少策略，以增强用户体验。

5.In clinical trials, a reduction of observation 观察减少 period can lead to faster drug approval.

在临床试验中，观察减少的周期可以加快药物批准速度。

作文

In the realm of scientific research, the concept of reduction of observation plays a crucial role in shaping our understanding of various phenomena. The term refers to the process of minimizing the number of observations or data points collected during an experiment or study. This can be done for several reasons, such as reducing costs, saving time, or focusing on specific variables that are believed to be more significant. However, while this approach can streamline research efforts, it also raises important questions about the validity and reliability of the findings.One of the primary advantages of reduction of observation is the efficiency it brings to the research process. In many cases, collecting vast amounts of data can be resource-intensive and time-consuming. By narrowing down the observations to only those that are essential, researchers can allocate their resources more effectively. For instance, in a clinical trial, instead of observing every possible side effect of a medication, researchers might choose to focus on the most common or severe reactions. This allows them to complete the study more quickly and get results that can lead to timely medical interventions.However, the reduction of observation can also lead to significant drawbacks. One major concern is that by limiting the scope of observations, researchers may overlook critical data that could influence the outcomes of their studies. For example, if a researcher only observes a small sample of participants in a psychological study, they may miss out on diverse perspectives and experiences that could provide a more comprehensive understanding of the issue at hand. Consequently, the findings may not be generalizable to the broader population, leading to potential biases and inaccuracies.Moreover, the reduction of observation can impact the reproducibility of research results. In scientific inquiry, the ability to replicate findings is fundamental to establishing credibility. If a study is based on a limited set of observations, other researchers may find it challenging to reproduce the results using different samples or methodologies. This can create a ripple effect, undermining the trustworthiness of the research community as a whole.To mitigate the risks associated with reduction of observation, researchers must carefully consider their study design and the implications of limiting data collection. It is essential to strike a balance between efficiency and thoroughness. Employing robust statistical methods can help in analyzing smaller datasets while still drawing meaningful conclusions. Additionally, researchers should be transparent about their data collection processes and openly discuss any limitations that arise from reduced observations.In conclusion, the reduction of observation is a double-edged sword in the field of research. While it can enhance efficiency and expedite the research process, it also poses significant risks to the validity and reliability of findings. As scientists continue to navigate the complexities of data collection, it is imperative that they remain vigilant about the potential pitfalls of reducing observations and strive for a balanced approach that prioritizes both efficiency and accuracy. Ultimately, the goal of research is to contribute valuable knowledge to society, and this requires a commitment to rigorous and comprehensive observation practices.

在科学研究领域，观察减少的概念在塑造我们对各种现象的理解中发挥着至关重要的作用。这个术语指的是在实验或研究过程中最小化收集的观察或数据点的数量。这可以出于多种原因，例如降低成本、节省时间或专注于被认为更重要的特定变量。然而，尽管这种方法可以简化研究工作，但它也引发了关于研究结果有效性和可靠性的重大问题。观察减少的主要优点之一是它为研究过程带来的效率。在许多情况下，收集大量数据可能会消耗资源并占用时间。通过将观察范围缩小到仅那些必要的观察，研究人员可以更有效地分配他们的资源。例如，在临床试验中，研究人员可能不会观察药物的每一种可能副作用，而是选择专注于最常见或最严重的反应。这使他们能够更快地完成研究，并获得可以导致及时医疗干预的结果。然而，观察减少也可能导致显著的缺点。一个主要的担忧是，通过限制观察的范围，研究人员可能会忽视可能影响研究结果的重要数据。例如，如果一位研究者只观察心理学研究中的少量参与者，他们可能会错过多样的观点和经历，这可能提供对当前问题的更全面理解。因此，研究结果可能无法推广到更广泛的人群，导致潜在的偏见和不准确性。此外，观察减少还会影响研究结果的可重复性。在科学探究中，复制研究结果的能力是建立可信度的基础。如果一项研究基于有限的观察集，其他研究人员可能会发现很难使用不同的样本或方法来复制结果。这可能会产生连锁反应，破坏整个研究社区的可信度。为了减轻与观察减少相关的风险，研究人员必须仔细考虑他们的研究设计以及限制数据收集的影响。找到效率和全面性之间的平衡至关重要。采用稳健的统计方法可以帮助分析较小的数据集，同时仍然得出有意义的结论。此外，研究人员应对其数据收集过程保持透明，公开讨论由于减少观察而产生的任何限制。总之，观察减少在研究领域是一把双刃剑。虽然它可以提高效率，加快研究进程，但它也对研究结果的有效性和可靠性构成了重大风险。随着科学家们继续应对数据收集的复杂性，他们必须对减少观察的潜在陷阱保持警惕，并努力寻求优先考虑效率和准确性的平衡方法。最终，研究的目标是为社会贡献有价值的知识，这需要对严格和全面的观察实践的承诺。