quintuplicated

简明释义

英[kwɪnˈtjuːplɪkət]美[kwɪnˈtʊplɪkɪt]

adj. 五倍的；一式五份的

v. 将……乘以五；把……制五份复印本

n. 一式五份中的一份；五个一组

第 三 人 称 单 数 q u i n t u p l i c a t e s

现 在 分 词 q u i n t u p l i c a t i n g

过 去 式 q u i n t u p l i c a t e d

过 去 分 词 q u i n t u p l i c a t e d

英英释义

单词用法

同义词

反义词

例句

1.In our study, each sample was quintuplicated to validate the findings.

在我们的研究中，每个样本都被五重复制以验证结果。

2.The artist created a quintuplicated series of prints to meet the high demand.

艺术家创作了一系列五重复制的版画以满足高需求。

3.The data was quintuplicated, meaning it was replicated five times for accuracy.

数据被五重复制，意味着它被复制了五次以确保准确性。

4.After the experiment, we found that the results were quintuplicated to ensure reliability.

实验结束后，我们发现结果被五重复制以确保可靠性。

5.The software generated a quintuplicated backup of all files to prevent data loss.

软件生成了所有文件的五重复制备份以防止数据丢失。

作文

In the realm of data analysis, the ability to manipulate and interpret large datasets is crucial. One interesting phenomenon that often occurs in statistical studies is when results are quintuplicated, meaning they are repeated five times or appear in five different iterations. This can happen due to various reasons, such as sampling errors, biases in data collection, or even intentional replication for validation purposes. Understanding why results might be quintuplicated can provide significant insights into the reliability of the findings. For instance, consider a research study aimed at understanding consumer behavior in the tech industry. If the researchers collected data from five different regions but used the same survey questions and methodology, they might find that certain trends are quintuplicated. This could indicate a strong consensus among consumers regarding their preferences for specific products. However, it could also suggest that the study lacks diversity in its sample population, potentially skewing the results. Moreover, when results are quintuplicated, it raises questions about the uniqueness of the data. Are the findings genuinely reflective of varied consumer choices, or are they merely echoing the same sentiments across different demographics? This is where critical thinking comes into play. Researchers must dissect the data carefully and consider whether the quintuplicated results are a product of genuine trends or simply artifacts of their methodology. In another scenario, let’s say a pharmaceutical company conducts clinical trials for a new medication. If the trial results show that the drug is effective in five separate studies, these outcomes could be viewed as quintuplicated evidence supporting the drug's efficacy. However, the scientific community would still demand rigorous scrutiny to ensure that these results are not coincidental or the result of flawed experimental design. The concept of quintuplicated results, therefore, serves as a double-edged sword. While it may bolster the credibility of a study, it also necessitates a deeper investigation into the methodologies employed. Furthermore, the significance of quintuplicated data extends beyond just academic research. In business, for example, companies often rely on market research that may yield quintuplicated insights about customer preferences. If a company discovers through multiple surveys that customers consistently prefer a particular feature in their products, this quintuplicated feedback can drive product development and marketing strategies. However, businesses must also be cautious; relying solely on quintuplicated data without considering other factors could lead to misguided decisions. In conclusion, the term quintuplicated encapsulates an essential aspect of data analysis and interpretation. Whether in academic research, clinical trials, or business strategies, recognizing the implications of quintuplicated results is vital. It prompts analysts and decision-makers to question the validity and reliability of their findings while encouraging a more nuanced approach to data interpretation. By understanding the significance of quintuplicated data, we can enhance our analytical skills and make better-informed decisions in various fields.

在数据分析领域，操纵和解释大型数据集的能力至关重要。在统计研究中，结果经常出现的一个有趣现象是当结果被五重重复时，意味着它们被重复五次或出现在五个不同的迭代中。这可能由于多种原因而发生，例如抽样错误、数据收集中的偏差，甚至是为了验证目的而进行的故意重复。理解结果为何可能被五重重复可以为发现的可靠性提供重要见解。例如，考虑一项旨在了解科技行业消费者行为的研究。如果研究人员从五个不同地区收集数据，但使用相同的调查问题和方法，他们可能会发现某些趋势被五重重复。这可能表明消费者对特定产品的偏好存在强烈共识。然而，它也可能表明该研究在样本人口上缺乏多样性，从而可能扭曲结果。此外，当结果被五重重复时，这引发了对数据独特性的质疑。这些发现是否真正反映了多样化的消费者选择，还是仅仅在不同的人群中回响同样的情绪？这就是批判性思维发挥作用的地方。研究人员必须仔细剖析数据，考虑五重重复的结果是否是由真实趋势产生的，还是仅仅是他们的方法论的产物。在另一个场景中，假设一家制药公司进行新药的临床试验。如果试验结果显示该药物在五个独立研究中有效，这些结果可以被视为支持药物疗效的五重重复证据。然而，科学界仍然会要求严格审查，以确保这些结果不是偶然的，或者是实验设计缺陷的结果。因此，五重重复结果的概念就像一把双刃剑。虽然它可能增强研究的可信度，但也需要对所采用的方法进行更深入的调查。此外，五重重复数据的重要性不仅限于学术研究。在商业中，例如，企业通常依赖市场研究，可能会产生关于客户偏好的五重重复见解。如果一家公司通过多项调查发现客户始终偏爱其产品中的某一特征，这种五重重复反馈可以推动产品开发和营销策略。然而，企业也必须保持谨慎；仅依赖五重重复数据而不考虑其他因素可能导致误导性决策。总之，术语五重重复概括了数据分析和解释的一个重要方面。无论是在学术研究、临床试验还是商业策略中，认识到五重重复结果的含义至关重要。它促使分析师和决策者质疑发现的有效性和可靠性，同时鼓励对数据解释采取更细致的方法。通过理解五重重复数据的重要性，我们可以增强我们的分析技能，并在各个领域做出更明智的决策。