observed data

简明释义

观测数据

英英释义

例句

1.The researchers collected observed data from various participants to analyze their behavior patterns.

研究人员收集了来自不同参与者的观察数据以分析他们的行为模式。

2.In the experiment, the observed data showed a significant increase in temperature over time.

实验中，观察数据显示温度随时间显著上升。

3.The observed data from the survey revealed important insights about consumer preferences.

调查中的观察数据揭示了关于消费者偏好的重要见解。

4.By analyzing the observed data, scientists were able to identify trends in climate change.

通过分析观察数据，科学家能够识别气候变化的趋势。

5.The observed data indicated that the new medication had a higher success rate than the previous one.

观察数据表明新药物的成功率高于之前的药物。

作文

In the realm of scientific research and data analysis, the term observed data refers to the information that has been collected through direct observation or measurement. This type of data is crucial because it forms the foundation upon which hypotheses are tested and theories are built. For instance, in a study examining the effects of a new drug on blood pressure, the observed data would consist of the actual blood pressure readings taken from participants before and after administering the drug. This data is vital for determining whether the drug has a significant effect on lowering blood pressure.The reliability of observed data is paramount in research. Researchers must ensure that their methods of observation are accurate and consistent. Any errors in measurement can lead to incorrect conclusions. For example, if a researcher uses a faulty blood pressure monitor, the observed data collected may not reflect the true effects of the drug. Therefore, it is essential to use calibrated instruments and standardized procedures when collecting observed data.Moreover, observed data can be influenced by various external factors. In social sciences, for instance, the behavior of individuals can change based on the environment or context in which they are observed. This phenomenon is known as the Hawthorne effect, where individuals modify their behavior because they know they are being studied. Consequently, researchers must take these variables into account when analyzing observed data, as they can skew results and lead to misleading interpretations.Another important aspect of observed data is its role in statistical analysis. Once data is collected, researchers often employ statistical methods to analyze the observed data and draw conclusions. This analysis can help identify patterns, correlations, and potential causations within the data. For example, if a researcher observes a consistent decrease in blood pressure readings among participants who took the new drug compared to those who did not, they may conclude that there is a relationship between the drug and reduced blood pressure.However, it is crucial to remember that correlation does not imply causation. Just because two variables appear to be related in the observed data does not mean that one causes the other. Researchers must conduct further studies and analyses to establish causative relationships. This can involve controlled experiments, longitudinal studies, or additional observational research.In summary, observed data is a fundamental component of scientific inquiry and analysis. It provides the empirical evidence needed to support or refute hypotheses and theories. However, researchers must approach the collection and analysis of observed data with caution, ensuring accuracy and accounting for potential biases. By doing so, they can contribute valuable insights to their respective fields and advance our understanding of complex phenomena. Ultimately, the integrity of observed data is essential for the advancement of knowledge and the development of effective solutions to real-world problems.

在科学研究和数据分析领域，术语observed data（观察数据）指的是通过直接观察或测量收集的信息。这种类型的数据至关重要，因为它构成了假设检验和理论建立的基础。例如，在研究一种新药对血压影响的过程中，observed data（观察数据）将包括在给药前后从参与者那里获得的实际血压读数。这些数据对于确定该药物是否对降低血压有显著效果至关重要。observed data（观察数据）的可靠性在研究中至关重要。研究人员必须确保他们的观察方法准确且一致。任何测量错误都可能导致错误的结论。例如，如果研究人员使用故障的血压监测仪，则收集到的observed data（观察数据）可能无法反映药物的真实效果。因此，在收集observed data（观察数据）时，使用经过校准的仪器和标准化程序至关重要。此外，observed data（观察数据）可能会受到各种外部因素的影响。在社会科学中，例如，个体的行为可能会根据观察他们的环境或上下文而改变。这种现象被称为霍桑效应，即个体因为知道自己正在被研究而修改其行为。因此，研究人员在分析observed data（观察数据）时，必须考虑这些变量，因为它们可能扭曲结果并导致误导性的解释。observed data（观察数据）的另一个重要方面是它在统计分析中的作用。一旦数据被收集，研究人员通常会采用统计方法来分析observed data（观察数据）并得出结论。这种分析可以帮助识别数据中的模式、相关性和潜在因果关系。例如，如果研究人员观察到服用新药的参与者的血压读数持续降低，而未服用药物的参与者则没有，他们可能会得出药物与降低血压之间存在关系的结论。然而，必须记住，相关性并不意味着因果关系。仅仅因为两个变量在observed data（观察数据）中似乎相关，并不意味着一个导致另一个。研究人员必须进行进一步的研究和分析，以建立因果关系。这可能涉及对照实验、纵向研究或其他观察性研究。总之，observed data（观察数据）是科学探究和分析的基本组成部分。它提供了支持或反驳假设和理论所需的实证证据。然而，研究人员在收集和分析observed data（观察数据）时必须谨慎行事，确保准确性并考虑潜在的偏见。通过这样做，他们可以为各自领域贡献有价值的见解，推动我们对复杂现象的理解。最终，observed data（观察数据）的完整性对于知识的进步和有效解决现实问题的发展至关重要。