probable error

简明释义

概率误差或然误差

英英释义

例句

1.The scientist calculated the probable error to determine the accuracy of his measurements.

科学家计算了可能误差以确定他的测量的准确性。

2.When conducting experiments, researchers must account for the probable error in their calculations.

在进行实验时，研究人员必须在计算中考虑可能误差。

3.A lower probable error indicates a higher precision in the experimental results.

较低的可能误差表示实验结果的精确度更高。

4.The report included a section on the probable error associated with the survey results.

报告中包含了一部分关于调查结果相关的可能误差。

5.In statistics, understanding the probable error helps in assessing the reliability of data.

在统计学中，理解可能误差有助于评估数据的可靠性。

作文

In the realm of statistics and data analysis, the term probable error refers to a measure of the accuracy of a statistical estimate. It is defined as the range within which we can expect the true value of a parameter to lie, with a certain level of confidence. Understanding this concept is crucial for researchers and analysts who rely on data to make informed decisions. The probable error helps in quantifying uncertainty and variability in data, allowing for more robust conclusions.For instance, when conducting an experiment or survey, researchers often collect data from a sample rather than the entire population. This sampling process introduces variability, and thus, the results may not perfectly reflect the true characteristics of the population. The probable error provides a statistical framework to account for this variability. By calculating the probable error, researchers can express how much error they might expect in their estimates, which is particularly important in fields such as medicine, psychology, and social sciences.One common application of probable error is in the context of estimating population means. If a researcher finds that the average height of a sample of individuals is 170 cm, the probable error can help indicate that the true average height of the entire population might be within a certain range, say 168 cm to 172 cm, with a specified level of confidence. This allows stakeholders to understand the reliability of the findings and make decisions based on a clear understanding of the potential for error.Furthermore, the probable error is not just limited to mean estimates; it can also apply to other statistical measures, such as proportions and regression coefficients. For example, in a political poll, if a candidate is reported to have 60% support with a probable error of ±3%, it means that the actual support could realistically range from 57% to 63%. This information is vital for campaign strategists who need to gauge the effectiveness of their efforts and adjust their strategies accordingly.Another important aspect of probable error is its role in hypothesis testing. In inferential statistics, researchers often formulate null and alternative hypotheses to test assumptions about a population. The probable error can help determine whether the observed data provide sufficient evidence to reject the null hypothesis. A smaller probable error indicates greater precision in the estimates, leading to more reliable conclusions.In conclusion, the concept of probable error is a fundamental component of statistical analysis that aids in understanding the reliability of estimates derived from sample data. It allows researchers to quantify uncertainty and communicate the degree of confidence in their findings. By incorporating the probable error into their analyses, researchers can provide clearer insights and make better-informed decisions based on their data. As we continue to navigate a world increasingly driven by data, mastering the understanding of probable error will be essential for anyone involved in research or data analysis.

在统计和数据分析领域，术语probable error指的是统计估计的准确性度量。它被定义为我们可以期望某个参数的真实值在一定置信水平内落入的范围。理解这一概念对于依赖数据做出明智决策的研究人员和分析师至关重要。probable error有助于量化数据中的不确定性和变异性，从而得出更稳健的结论。例如，在进行实验或调查时，研究人员通常从样本中收集数据，而不是整个总体。这个抽样过程引入了变异性，因此，结果可能无法完美反映总体的真实特征。probable error提供了一个统计框架，以考虑这种变异性。通过计算probable error，研究人员可以表达他们在估计中可能预期的误差，这在医学、心理学和社会科学等领域尤其重要。probable error的一个常见应用是在估计总体均值的情况下。如果一位研究人员发现一组个体的平均身高为170厘米，则probable error可以帮助表明整个总体的真实平均身高可能在某个范围内，例如168厘米到172厘米，并具有指定的置信水平。这使利益相关者能够理解研究结果的可靠性，并根据对潜在误差的清晰理解做出决策。此外，probable error不仅限于均值估计；它还可以适用于其他统计量，例如比例和回归系数。例如，在政治民调中，如果一位候选人的支持率被报告为60%，而probable error为±3%，这意味着实际支持率实际上可能在57%到63%之间。这些信息对于需要评估努力效果并相应调整策略的竞选战略家至关重要。probable error的另一个重要方面是它在假设检验中的作用。在推断统计中，研究人员通常制定零假设和备择假设，以测试对总体的假设。probable error可以帮助确定观察到的数据是否提供足够的证据来拒绝零假设。较小的probable error表示估计的精确度更高，从而导致更可靠的结论。总之，probable error的概念是统计分析的基本组成部分，有助于理解从样本数据得出的估计的可靠性。它使研究人员能够量化不确定性并传达对其发现的置信程度。通过将probable error纳入分析，研究人员可以提供更清晰的见解，并根据数据做出更明智的决策。随着我们继续在一个日益以数据驱动的世界中航行，掌握对probable error的理解对任何参与研究或数据分析的人来说都将是必不可少的。