per sample

简明释义

根据样品

英英释义

例句

1.The lab charges $50 per sample for testing.

实验室每个样本的测试费用为50美元。

2.The report indicates an average of 10 results per sample analyzed.

报告显示每个样本分析的平均结果为10个。

3.We need to collect data per sample to ensure accuracy.

我们需要每个样本收集数据以确保准确性。

4.The pricing model is based on $20 per sample processed.

定价模型基于每个样本处理20美元。

5.Please provide a detailed description per sample submitted.

请提供每个提交的样本的详细描述。

作文

In the field of scientific research, data analysis plays a crucial role in deriving meaningful conclusions from experiments. One important aspect of data analysis is understanding how to interpret results per sample. This term refers to the value or measurement obtained from each individual sample collected during an experiment. For instance, if a researcher is studying the effects of a new drug on blood pressure, they might collect blood pressure readings from multiple participants. The data collected per sample allows the researcher to assess the variability and effectiveness of the drug across different individuals.When analyzing data per sample, it is essential to ensure that the samples are representative of the larger population. This means that the samples should reflect the diversity and characteristics of the group being studied. If the samples are biased or not representative, the conclusions drawn from the data may be misleading. Therefore, researchers often employ random sampling techniques to select participants, ensuring that each individual has an equal chance of being included in the study.Moreover, calculating averages or other statistical measures per sample can provide insights into trends and patterns within the data. For example, if the average blood pressure reading per sample shows a significant decrease after administering the drug, it could indicate that the medication is effective. However, it is also important to consider the standard deviation per sample to understand the variability in the data. A low standard deviation suggests that the data points are close to the mean, while a high standard deviation indicates a wider spread of values.In addition, researchers often present their findings in graphs or charts, highlighting the results per sample. Visual representation of data can make it easier for others to understand the implications of the research. For instance, a bar graph showing the average blood pressure per sample before and after treatment can effectively convey the drug’s impact at a glance.Furthermore, the concept of per sample extends beyond just numerical data. In qualitative research, where data is collected through interviews or observations, the insights gained per sample can reveal deeper understanding of participants’ experiences and perspectives. Analyzing responses per sample allows researchers to identify common themes or unique viewpoints that contribute to the overall narrative of the study.In conclusion, the term per sample is fundamental to data analysis in both quantitative and qualitative research. It emphasizes the importance of examining individual measurements or insights to draw broader conclusions. By carefully considering the data per sample, researchers can ensure that their findings are robust, reliable, and applicable to the larger population. Whether in the context of medical research, social sciences, or any other field, the ability to analyze and interpret data per sample is a vital skill for any researcher aiming to contribute valuable knowledge to their discipline.

在科学研究领域，数据分析在从实验中得出有意义的结论方面起着至关重要的作用。数据分析的一个重要方面是理解如何解释结果每个样本。这个术语指的是在实验过程中从每个单独收集的样本中获得的值或测量。例如，如果研究人员正在研究一种新药对血压的影响，他们可能会收集多个参与者的血压读数。收集的数据每个样本使研究人员能够评估药物在不同个体中的变异性和有效性。在分析数据时每个样本，确保样本具有代表性是至关重要的。这意味着样本应反映被研究群体的多样性和特征。如果样本存在偏差或不具代表性，从数据中得出的结论可能会误导。因此，研究人员通常采用随机抽样技术来选择参与者，确保每个人都有相等的机会被纳入研究。此外，计算平均值或其他统计指标每个样本可以提供对数据中的趋势和模式的洞察。例如，如果平均血压读数每个样本在施用药物后显示显著下降，这可能表明该药物有效。然而，还需要考虑标准差每个样本以了解数据的变异性。较低的标准差表明数据点接近均值，而较高的标准差则表示值的分布更广。此外，研究人员通常通过图表或图形呈现他们的发现，突出显示数据每个样本的结果。数据的可视化表示可以使他人更容易理解研究的含义。例如，显示治疗前后平均血压的条形图每个样本可以有效地传达药物的影响。此外，每个样本的概念不仅限于数值数据。在定性研究中，通过访谈或观察收集的数据，获得的见解每个样本可以揭示参与者经历和观点的更深层次理解。分析响应每个样本使研究人员能够识别出共同主题或独特观点，这些观点有助于研究整体叙述。总之，术语每个样本是定量和定性研究中数据分析的基础。它强调了检查单个测量或见解以得出更广泛结论的重要性。通过仔细考虑数据每个样本，研究人员可以确保他们的发现是稳健、可靠且适用于更大的人群。无论是在医学研究、社会科学还是其他任何领域，分析和解释数据的能力每个样本是任何希望为其学科贡献有价值知识的研究人员必备的技能。