empiric data

简明释义

经验资料

英英释义

例句

1.In clinical trials, empiric data is crucial for determining the effectiveness of a new drug.

在临床试验中，经验数据对确定新药的有效性至关重要。

2.The scientist relied on empiric data to support his hypothesis.

科学家依赖于经验数据来支持他的假设。

3.The report was based on empiric data collected over several years.

该报告基于数年收集的经验数据。

4.Using empiric data, the team was able to identify trends in consumer behavior.

利用经验数据，团队能够识别消费者行为中的趋势。

5.The researchers gathered empiric data through extensive field studies.

研究人员通过广泛的实地研究收集了经验数据。

作文

In the realm of scientific research and decision-making, the importance of empiric data cannot be overstated. This term refers to information acquired through observation or experimentation rather than theory or pure logic. Empiric data plays a crucial role in validating hypotheses and theories, allowing researchers to draw conclusions based on real-world evidence. For instance, in the field of medicine, clinical trials rely heavily on empiric data to assess the effectiveness of new treatments. By collecting data from patients, researchers can determine whether a particular drug has a positive impact on health outcomes. This process not only enhances our understanding of medical science but also ensures that patients receive treatments that have been proven to work based on empiric data.Moreover, empiric data is essential in social sciences, where researchers study human behavior and societal trends. Surveys and observational studies are common methods used to gather empiric data. For example, sociologists might conduct interviews or distribute questionnaires to collect information about people's attitudes towards climate change. The insights gained from this empiric data can inform public policy and contribute to more effective strategies for addressing environmental issues.The reliance on empiric data also extends to fields such as economics. Economists analyze various indicators, including employment rates and consumer spending, to understand economic trends and make forecasts. By examining empiric data, they can identify patterns and correlations that help explain the complexities of economic systems. This data-driven approach allows for more informed decision-making by governments and businesses alike.However, it is important to recognize that empiric data is not without its limitations. The quality of empiric data can vary significantly depending on the methods used to collect it. Poorly designed studies or biased sampling can lead to inaccurate conclusions. Therefore, researchers must be diligent in their methodology to ensure the reliability of the empiric data they gather. Additionally, while empiric data provides valuable insights, it is often necessary to complement it with theoretical frameworks to fully understand complex phenomena.In conclusion, empiric data serves as the backbone of scientific inquiry across various disciplines. Its significance lies in its ability to provide concrete evidence that supports or refutes theories. As we continue to navigate an increasingly data-driven world, the role of empiric data will only grow in importance. Researchers, policymakers, and practitioners must prioritize the collection and analysis of high-quality empiric data to make informed decisions that positively impact society. Ultimately, embracing the value of empiric data can lead to advancements in knowledge and improvements in various aspects of life, from healthcare to environmental protection.

在科学研究和决策的领域中，empiric data的重要性不容小觑。这个术语指的是通过观察或实验获得的信息，而非理论或纯逻辑。empiric data在验证假设和理论方面发挥着至关重要的作用，使研究人员能够基于现实世界的证据得出结论。例如，在医学领域，临床试验在评估新治疗方法的有效性时，极度依赖于empiric data。通过收集患者的数据，研究人员可以确定特定药物对健康结果是否有积极影响。这一过程不仅增强了我们对医学科学的理解，还确保患者接受经过empiric data证明有效的治疗。此外，empiric data在社会科学中也是必不可少的，研究人员研究人类行为和社会趋势。调查和观察研究是收集empiric data的常用方法。例如，社会学家可能会进行访谈或分发问卷，以收集关于人们对气候变化态度的信息。从这些empiric data中获得的见解可以为公共政策提供信息，并有助于制定更有效的应对环境问题的策略。对empiric data的依赖还扩展到经济学等领域。经济学家分析各种指标，包括就业率和消费者支出，以了解经济趋势并做出预测。通过检查empiric data，他们可以识别帮助解释经济系统复杂性的模式和相关性。这种数据驱动的方法使政府和企业能够做出更明智的决策。然而，重要的是要认识到，empiric data并非没有局限性。根据收集数据的方法，empiric data的质量可能会有所不同。设计不良的研究或有偏见的抽样可能导致不准确的结论。因此，研究人员必须在方法论上保持谨慎，以确保所收集的empiric data的可靠性。此外，虽然empiric data提供了宝贵的见解，但通常需要与理论框架相结合，以充分理解复杂现象。总之，empiric data作为各个学科科学探究的支柱，其重要性在于其能够提供支持或反驳理论的具体证据。随着我们继续在一个日益数据驱动的世界中航行，empiric data的作用只会越来越重要。研究人员、政策制定者和从业者必须优先考虑高质量empiric data的收集和分析，以做出对社会产生积极影响的明智决策。最终，拥抱empiric data的价值可以促进知识的进步，并改善生活的各个方面，从医疗保健到环境保护。