consistency of estimate

简明释义

估计值的一致性

英英释义

例句

1.The consistency of estimate across different surveys indicates reliable results.

不同调查之间的估算一致性表明结果可靠。

2.The auditor raised concerns about the consistency of estimate in the quarterly projections.

审计师对季度预测中估算的一致性表示担忧。

3.To improve the consistency of estimate, we standardized our data collection methods.

为了提高估算的一致性，我们标准化了数据收集方法。

4.We need to check the consistency of estimate before finalizing the financial report.

在最终确定财务报告之前，我们需要检查估算的一致性。

5.The team conducted a review to ensure the consistency of estimate in their project budget.

团队进行了审查，以确保他们项目预算的估算一致性。

作文

In the field of statistics and data analysis, the term consistency of estimate refers to the property of an estimator to converge in probability to the true value of the parameter being estimated as the sample size increases. This concept is crucial for ensuring that the conclusions drawn from statistical analyses are reliable and valid. When we say that an estimator is consistent, we imply that as we collect more data, our estimates become more accurate and closer to the actual population parameter. For example, consider a scenario where researchers are trying to estimate the average height of adult males in a city. They might start by taking a small sample of 30 individuals and calculating the mean height. If they repeat this process with larger samples—say, 100, 500, or even 1,000 individuals—their calculated mean should ideally approach the true average height of all adult males in that city. This behavior exemplifies the consistency of estimate (估计的一致性), which assures researchers that their methods are sound and their findings are credible.The importance of consistency of estimate extends beyond just theoretical understanding; it has practical implications in various fields such as economics, medicine, and social sciences. For instance, in clinical trials, if a new drug's effectiveness is estimated using a small sample size, the results may vary significantly from what would be observed in the general population. However, as the sample size increases, the estimates of the drug's efficacy become more stable and trustworthy, demonstrating the consistency of estimate (估计的一致性) in action.Moreover, the consistency of estimate is often assessed through techniques like the Law of Large Numbers, which states that as the number of trials increases, the average of the results will converge to the expected value. This principle reassures statisticians that their estimators will provide reliable results as more data is gathered. On the other hand, it is also essential to recognize that not all estimators possess this property. Some estimators may be biased or inconsistent, leading to inaccurate conclusions. For example, if certain data points are systematically excluded from the analysis, the resulting estimates may not reflect the true population characteristics, highlighting the need for careful data collection and analysis practices. In conclusion, the consistency of estimate (估计的一致性) is a fundamental concept in statistics that ensures the reliability of estimators as sample sizes increase. It plays a vital role in various research fields, providing a framework for making informed decisions based on data analysis. By understanding and applying this concept, researchers can enhance the credibility of their findings and contribute to the advancement of knowledge across disciplines. Therefore, maintaining the consistency of estimate (估计的一致性) is not only a statistical requirement but also a cornerstone of effective research methodology.

在统计学和数据分析领域，术语consistency of estimate（估计的一致性）指的是一种估计量的特性，即随着样本量的增加，估计量在概率上收敛到所估计参数的真实值。这个概念对于确保从统计分析中得出的结论是可靠和有效的至关重要。当我们说一个估计量是一致的时，我们的意思是随着我们收集更多的数据，我们的估计变得更加准确，更接近实际的人口参数。例如，考虑一个研究人员试图估计一个城市成年男性的平均身高的场景。他们可能会首先抽取30个个体的小样本，并计算平均身高。如果他们以更大的样本重复这个过程——比如100、500甚至1000个个体——他们计算出的均值应该理想地接近该城市所有成年男性的真实平均身高。这种行为体现了consistency of estimate（估计的一致性），它向研究人员保证他们的方法是合理的，他们的发现是可信的。consistency of estimate（估计的一致性）的重要性不仅限于理论理解；它在经济学、医学和社会科学等多个领域具有实际意义。例如，在临床试验中，如果使用小样本量来估计新药的有效性，结果可能与在普通人群中观察到的结果有显著差异。然而，随着样本量的增加，对药物有效性的估计变得更加稳定和可靠，展示了consistency of estimate（估计的一致性）的实际应用。此外，consistency of estimate（估计的一致性）通常通过大数法则等技术进行评估，该法则指出，随着试验次数的增加，结果的平均值将收敛于期望值。这个原理使统计学家放心，他们的估计量在收集更多数据时将提供可靠的结果。另一方面，也必须认识到并非所有的估计量都具备这一特性。一些估计量可能存在偏差或不一致，导致不准确的结论。例如，如果某些数据点系统性地被排除在分析之外，所得到的估计可能无法反映真实的人口特征，这突显了谨慎的数据收集和分析实践的必要性。总之，consistency of estimate（估计的一致性）是统计学中的一个基本概念，它确保随着样本量的增加，估计量的可靠性。它在各个研究领域发挥着重要作用，为基于数据分析做出明智决策提供了框架。通过理解和应用这一概念，研究人员可以增强其发现的可信度，并推动跨学科知识的进步。因此，保持consistency of estimate（估计的一致性）不仅是统计学的要求，更是有效研究方法论的基石。