confidence interval

简明释义

置信区间

英英释义

例句

1.The survey results showed that the average income of the respondents falls within a confidence interval 置信区间 of $50,000 to $60,000.

调查结果显示，受访者的平均收入在$50,000到$60,000的置信区间内。

2.When conducting experiments, researchers often report a confidence interval 置信区间 to indicate the reliability of their findings.

在进行实验时，研究人员通常会报告一个置信区间以指示他们发现的可靠性。

3.In our study, we found that the mean height of adults in the city has a confidence interval 置信区间 of 5'5" to 5'9".

在我们的研究中，我们发现该市成年人的平均身高为5'5"到5'9"的置信区间。

4.A confidence interval 置信区间 provides a range of values that is likely to contain the population parameter.

一个置信区间提供了一个可能包含总体参数的值范围。

5.A narrower confidence interval 置信区间 indicates more precise estimates.

更窄的置信区间表示更精确的估计。

作文

In the realm of statistics, understanding the concept of a confidence interval is crucial for interpreting data accurately. A confidence interval is a range of values that is used to estimate the true value of a population parameter, such as a mean or proportion. This statistical tool provides a measure of uncertainty around the estimate, allowing researchers to express how confident they are in their findings. For instance, if a survey indicates that 60% of respondents favor a particular policy, the confidence interval might be reported as 60% ± 5%. This means that the researchers are confident that the true proportion of supporters lies between 55% and 65%.The importance of a confidence interval cannot be overstated, especially in fields such as medicine, economics, and social sciences, where decisions often rely on statistical data. By providing a range rather than a single point estimate, a confidence interval accounts for variability and uncertainty inherent in sample data. It helps to communicate the precision of an estimate and the potential error involved. For example, in clinical trials, a confidence interval can indicate the effectiveness of a new drug, guiding healthcare professionals in making informed decisions about treatment options.Moreover, the width of a confidence interval is influenced by several factors, including the sample size and the level of confidence chosen by the researcher. A larger sample size generally leads to a narrower confidence interval, reflecting more reliable estimates. Conversely, a smaller sample size may produce a wider confidence interval, indicating greater uncertainty. Researchers often select a confidence level, commonly set at 95%, which implies that if the same study were repeated multiple times, approximately 95% of the calculated confidence intervals would contain the true population parameter.Understanding confidence intervals also involves recognizing their limitations. While they provide valuable insights, they do not guarantee that the true parameter lies within the specified range. It is essential to interpret confidence intervals within the context of the study and consider other factors, such as sampling methods and potential biases. Additionally, the choice of confidence level can significantly impact the width of the confidence interval. A higher confidence level will yield a wider interval, which may reduce the precision of the estimate.In conclusion, mastering the concept of a confidence interval is vital for anyone engaged in research or data analysis. It serves as a fundamental tool for estimating population parameters and communicating the reliability of those estimates. By incorporating confidence intervals into their analyses, researchers can enhance the clarity and credibility of their findings, ultimately contributing to more informed decision-making processes. Whether in public health, policy-making, or scientific research, the role of confidence intervals is indispensable in navigating the complexities of data interpretation and ensuring that conclusions drawn from statistical analyses are both accurate and meaningful.

在统计学领域，理解置信区间的概念对于准确解读数据至关重要。置信区间是一个值的范围，用于估计某个总体参数的真实值，如均值或比例。这个统计工具提供了对估计值的不确定性的衡量，使研究人员能够表达他们对研究结果的信心。例如，如果一项调查显示60%的受访者支持某项政策，则置信区间可能报告为60% ± 5%。这意味着研究人员有信心真实的支持比例在55%到65%之间。置信区间的重要性不容小觑，尤其是在医学、经济学和社会科学等领域，决策往往依赖于统计数据。通过提供一个范围而不是单一的点估计，置信区间考虑到样本数据中固有的变异性和不确定性。它有助于传达估计的精确度和潜在的误差。例如，在临床试验中，置信区间可以指示新药的有效性，指导医疗专业人员在治疗选择上做出明智的决策。此外，置信区间的宽度受到多个因素的影响，包括样本大小和研究人员选择的置信水平。较大的样本大小通常会导致较窄的置信区间，反映出更可靠的估计。相反，较小的样本大小可能产生较宽的置信区间，表示更大的不确定性。研究人员通常选择一个置信水平，通常设定为95%，这意味着如果同一研究重复多次，约95%的计算出的置信区间将包含真实的总体参数。理解置信区间还需要认识到其局限性。虽然它们提供了有价值的见解，但并不能保证真实参数位于指定范围内。在解释置信区间时，必须结合研究的背景，并考虑其他因素，如抽样方法和潜在偏差。此外，置信水平的选择会显著影响置信区间的宽度。较高的置信水平将产生较宽的区间，这可能降低估计的精确度。总之，掌握置信区间的概念对于任何从事研究或数据分析的人来说都是至关重要的。它作为估计总体参数和传达这些估计可靠性的基本工具。通过将置信区间纳入分析，研究人员可以增强其发现的清晰度和可信度，最终促进更明智的决策过程。无论是在公共卫生、政策制定还是科学研究中，置信区间的作用在于导航数据解释的复杂性，确保从统计分析中得出的结论既准确又有意义。