arbitrary datum

简明释义

1. 任意起算值; 2. 任意基数;

英英释义

例句

1.In our experiment, we decided to use an arbitrary datum as a baseline for comparison.

在我们的实验中，我们决定使用一个任意数据作为比较的基线。

2.The researcher acknowledged that the choice of arbitrary datum impacted the overall findings.

研究人员承认，任意数据的选择影响了整体发现。

3.The results were skewed due to the selection of an arbitrary datum that did not represent the population accurately.

由于选择了一个不准确代表总体的任意数据，结果出现了偏差。

4.For this model, any arbitrary datum can be used as long as it is consistent throughout the analysis.

对于这个模型，只要在整个分析中保持一致，可以使用任何任意数据。

5.When analyzing the dataset, we found that using an arbitrary datum could lead to misleading conclusions.

在分析数据集时，我们发现使用一个任意数据可能导致误导性的结论。

作文

In the realm of data analysis and scientific research, the term arbitrary datum refers to a piece of information or data point that is selected without a specific reason or criterion. This concept can often lead to discussions about the validity and reliability of findings in various fields, including statistics, social sciences, and even natural sciences. Understanding the implications of using arbitrary datum is crucial for researchers and analysts alike.When conducting research, it is essential to rely on data that is collected systematically and with purpose. However, sometimes researchers may inadvertently include arbitrary datum in their studies. For instance, when measuring the effectiveness of a new drug, if a researcher selects participants based on convenience rather than a random sampling method, the data collected may include arbitrary datum that does not represent the broader population. This can skew results and lead to inaccurate conclusions.Moreover, the presence of arbitrary datum can affect the integrity of statistical analyses. When researchers perform analyses on data sets that contain arbitrary datum, they may find patterns or correlations that do not actually exist in the larger population. This phenomenon is known as data mining, where researchers might unintentionally discover misleading trends due to the inclusion of non-representative data points. Therefore, it is imperative for researchers to critically evaluate their data collection methods to minimize the impact of arbitrary datum.In the field of social sciences, the consequences of relying on arbitrary datum can be particularly significant. Social scientists often study complex human behaviors and societal trends, where the context and nuances are vital for accurate interpretation. If a researcher uses arbitrary datum from a biased sample, their findings could reinforce stereotypes or propagate misinformation. For example, if a survey on public opinion about a policy is conducted only among a specific demographic group, the results may not reflect the views of the entire population, leading to misguided policy decisions.To mitigate the risks associated with arbitrary datum, researchers should adopt rigorous methodologies that emphasize randomized sampling and comprehensive data collection strategies. By ensuring that data points are selected based on clear criteria and represent the population accurately, researchers can enhance the validity of their conclusions. Additionally, peer review processes can help identify potential biases in research that may arise from the use of arbitrary datum.In conclusion, while arbitrary datum may seem innocuous at first glance, its implications can be far-reaching in the context of research and data analysis. It is essential for researchers to be aware of the potential pitfalls associated with using arbitrary data points and to strive for methodological rigor in their work. By doing so, they can contribute to more reliable and valid findings that better inform our understanding of complex phenomena in various fields. Ultimately, the goal should always be to base conclusions on sound data that accurately reflects reality, free from the distortions introduced by arbitrary datum.

在数据分析和科学研究领域，术语arbitrary datum指的是选择没有特定理由或标准的信息或数据点。这个概念常常引发关于各个领域（包括统计学、社会科学甚至自然科学）研究结果的有效性和可靠性的讨论。理解使用arbitrary datum的影响对于研究人员和分析师来说至关重要。在进行研究时，依赖系统性和有目的地收集的数据是至关重要的。然而，有时研究人员可能会无意中在他们的研究中包含arbitrary datum。例如，在测量新药效果时，如果研究人员根据便利性而不是随机抽样方法选择参与者，则收集的数据可能包含不代表更广泛人群的arbitrary datum。这可能会扭曲结果并导致不准确的结论。此外，arbitrary datum的存在可能会影响统计分析的完整性。当研究人员对包含arbitrary datum的数据集进行分析时，他们可能会发现实际上在更大人群中并不存在的模式或相关性。这种现象被称为数据挖掘，研究人员可能无意中由于包含非代表性数据点而发现误导性的趋势。因此，研究人员必须批判性地评估他们的数据收集方法，以最小化arbitrary datum的影响。在社会科学领域，依赖arbitrary datum的后果尤其显著。社会科学家通常研究复杂的人类行为和社会趋势，其中背景和细微差别对于准确解释至关重要。如果研究人员使用来自偏见样本的arbitrary datum，他们的发现可能会加强刻板印象或传播错误信息。例如，如果对公众对某项政策的意见进行的调查仅在特定人口群体中进行，则结果可能无法反映整个群体的观点，从而导致误导性的政策决策。为了减轻与arbitrary datum相关的风险，研究人员应采用强调随机抽样和全面数据收集策略的严格方法论。通过确保数据点是基于明确标准选择的，并准确代表人群，研究人员可以增强其结论的有效性。此外，同行评审过程可以帮助识别可能因使用arbitrary datum而产生的研究偏见。总之，尽管arbitrary datum乍一看似乎无害，但在研究和数据分析的背景下，其影响可能是深远的。研究人员必须意识到使用任意数据点可能带来的潜在陷阱，并努力在工作中保持方法论的严谨性。通过这样做，他们可以为我们对各个领域复杂现象的理解提供更可靠和有效的发现。最终，目标应始终是基于反映现实的可靠数据得出结论，而不受arbitrary datum引入的扭曲。