raw sample

简明释义

粗油样

英英释义

例句

1.The lab technician prepared the raw sample for further testing.

实验室技术员准备了原始样本以进行进一步测试。

2.Before processing, we need to ensure the raw sample is free from contamination.

在处理之前，我们需要确保原始样本不受污染。

3.The researcher collected a raw sample to analyze the water quality.

研究人员收集了一个原始样本来分析水质。

4.We need to store the raw sample at low temperatures to preserve its integrity.

我们需要将原始样本储存在低温下以保持其完整性。

5.A raw sample of soil was taken to study its mineral composition.

取了一份土壤的原始样本以研究其矿物成分。

作文

In the world of scientific research and data analysis, the term raw sample refers to an unprocessed or unrefined collection of data or materials that have been gathered for the purpose of study. This is a crucial concept in various fields, including biology, chemistry, and social sciences, where researchers need to analyze information to draw meaningful conclusions. The significance of raw sample cannot be overstated, as it serves as the foundation upon which further analysis, interpretation, and conclusions are built.When scientists collect a raw sample, they are usually interested in obtaining a representation of a larger population or phenomenon. For instance, in environmental studies, a researcher might collect soil samples from different locations to understand the effects of pollution. These soil samples, in their original state, are considered raw samples until they undergo testing and analysis. The results derived from these raw samples can provide insights into the health of the ecosystem, the presence of contaminants, and even inform policy decisions regarding environmental protection.Similarly, in the field of psychology, researchers often rely on raw samples of data collected from surveys or experiments. For example, a psychologist might conduct a survey to gauge public opinion on a particular issue. The responses collected represent a raw sample of the population's views before any statistical methods are applied to interpret the data. By analyzing these raw samples, psychologists can identify trends, correlations, and potentially causal relationships among variables.However, working with raw samples comes with its challenges. One major concern is the potential for bias in the collection process. If a raw sample is not representative of the larger population, the conclusions drawn from it may be flawed. For instance, if a researcher only collects data from a specific demographic group without considering others, the findings may not accurately reflect the overall population. Therefore, it is essential for researchers to employ rigorous sampling methods to ensure that their raw samples are as unbiased and representative as possible.Once the raw samples have been collected, they typically undergo a series of processing steps to prepare them for analysis. This may involve cleaning the data, removing outliers, or applying statistical techniques to make sense of the information. It is during this stage that the raw samples transform into more refined datasets, allowing researchers to perform in-depth analyses and derive conclusions.In conclusion, the concept of raw sample is integral to the research process across various disciplines. It represents the initial stage of data collection, which is essential for drawing valid conclusions. Understanding the importance of collecting high-quality raw samples and the methods used to analyze them is crucial for anyone involved in research. By paying careful attention to the integrity of raw samples, researchers can ensure that their findings contribute valuable knowledge to their respective fields and ultimately benefit society as a whole.

在科学研究和数据分析的世界中，术语raw sample指的是为研究目的收集的未经处理或精炼的数据或材料。这是生物学、化学和社会科学等多个领域中的一个关键概念，研究人员需要分析信息以得出有意义的结论。raw sample的重要性不容小觑，因为它作为进一步分析、解释和得出结论的基础。当科学家收集raw sample时，他们通常希望获得更大人群或现象的代表。例如，在环境研究中，研究人员可能会从不同地点收集土壤样本，以了解污染的影响。这些土壤样本在其原始状态下被视为raw sample，直到它们经过测试和分析。从这些raw sample中得出的结果可以提供有关生态系统健康、污染物存在的见解，甚至为环境保护政策决策提供信息。同样，在心理学领域，研究人员通常依赖于从调查或实验中收集的raw sample数据。例如，心理学家可能会进行调查，以评估公众对特定问题的看法。收集的回应代表了人群观点的raw sample，在任何统计方法应用于解释数据之前。通过分析这些raw sample，心理学家可以识别趋势、相关性以及潜在的变量之间因果关系。然而，处理raw sample也面临着挑战。一个主要问题是收集过程中的偏见。如果raw sample不代表更大的人群，则从中得出的结论可能存在缺陷。例如，如果研究者只从特定人口群体收集数据而未考虑其他群体，发现可能无法准确反映整体人群。因此，研究人员必须采用严格的抽样方法，以确保他们的raw sample尽可能无偏见和具有代表性。一旦收集了raw sample，通常会经过一系列处理步骤，以准备它们进行分析。这可能涉及清理数据、去除异常值或应用统计技术来理解信息。正是在这一阶段，raw sample转变为更精炼的数据集，使研究人员能够进行深入分析并得出结论。总之，raw sample的概念在各个学科的研究过程中都是不可或缺的。它代表了数据收集的初始阶段，这对于得出有效的结论至关重要。理解收集高质量raw sample的重要性以及分析它们所使用的方法，对于任何参与研究的人来说都是至关重要的。通过仔细关注raw sample的完整性，研究人员可以确保他们的发现为各自领域贡献有价值的知识，并最终使整个社会受益。