statistical estimation

简明释义

统计估计

英英释义

例句

1.The statistical estimation of survey results allows companies to make informed decisions.

调查结果的统计估计使公司能够做出明智的决策。

2.Economists rely on statistical estimation to analyze economic trends and forecasts.

经济学家依赖于统计估计来分析经济趋势和预测。

3.Using statistical estimation, scientists can assess the reliability of their experimental results.

科学家可以使用统计估计来评估实验结果的可靠性。

4.The researchers used statistical estimation to predict the population growth for the next decade.

研究人员使用统计估计来预测未来十年的人口增长。

5.In quality control, statistical estimation helps determine the average defect rate in production.

在质量控制中，统计估计有助于确定生产中的平均缺陷率。

作文

Statistical estimation is a fundamental concept in the field of statistics that plays a crucial role in data analysis and decision-making processes. It involves using sample data to make inferences or predictions about a larger population. For instance, if a researcher wants to understand the average height of adult men in a city, they may not be able to measure every individual. Instead, they can take a random sample of men, measure their heights, and then use statistical estimation (统计估计) techniques to estimate the average height of all adult men in that city.The process of statistical estimation (统计估计) typically begins with collecting data through surveys or experiments. Once the data is collected, statisticians apply various methods to analyze it. These methods can include point estimation, where a single value is calculated as an estimate of a population parameter, and interval estimation, which provides a range of values within which the parameter is likely to fall. Both methods are essential for understanding the reliability and accuracy of the estimates produced.One of the key components of statistical estimation (统计估计) is the concept of sampling. A well-chosen sample can lead to more accurate and reliable estimates. Random sampling is often preferred because it minimizes bias and ensures that every member of the population has an equal chance of being selected. However, challenges such as sample size and variability must also be considered. A larger sample size generally leads to more precise estimates, but it can also require more time and resources.Another important aspect of statistical estimation (统计估计) is the evaluation of estimation methods. Statisticians often use metrics like bias, consistency, and efficiency to assess the quality of an estimator. Bias refers to the difference between the expected value of the estimator and the true value of the parameter being estimated. Consistency indicates whether the estimator converges to the true parameter value as the sample size increases, while efficiency measures how well the estimator uses the information available in the data.Moreover, statistical estimation (统计估计) is not limited to descriptive statistics; it also plays a significant role in inferential statistics. Inferential statistics allows researchers to draw conclusions about a population based on sample data, which is particularly useful in fields such as medicine, social sciences, and economics. For example, clinical trials often rely on statistical estimation (统计估计) to determine the effectiveness of new drugs by comparing outcomes between treatment groups and control groups.In conclusion, statistical estimation (统计估计) is a vital tool in the world of data analysis, enabling researchers to make informed decisions based on limited information. Its applications are vast and varied, impacting numerous fields and industries. By understanding the principles and methodologies behind statistical estimation (统计估计), individuals and organizations can harness the power of data to drive progress and innovation.

统计估计是统计学领域的一个基本概念，在数据分析和决策过程中发挥着至关重要的作用。它涉及使用样本数据对更大的人群进行推断或预测。例如，如果一位研究人员想了解某城市成年男性的平均身高，他们可能无法测量每个个体。相反，他们可以随机抽取一些男性，测量他们的身高，然后使用统计估计（统计估计）技术来估算该城市所有成年男性的平均身高。统计估计（统计估计）的过程通常始于通过调查或实验收集数据。一旦数据被收集，统计学家就会应用各种方法进行分析。这些方法可以包括点估计，其中计算一个值作为总体参数的估计，以及区间估计，它提供一个范围，参数很可能落在其中。这两种方法对于理解所产生估计的可靠性和准确性至关重要。统计估计（统计估计）的一个关键组成部分是抽样的概念。精心选择的样本可以导致更准确和可靠的估计。随机抽样通常是首选，因为它最小化偏差，并确保总体中的每个成员都有相等的被选中机会。然而，样本大小和变异性等挑战也必须考虑。较大的样本大小通常会导致更精确的估计，但它也可能需要更多的时间和资源。统计估计（统计估计）的另一个重要方面是对估计方法的评估。统计学家通常使用偏差、一致性和效率等指标来评估估计器的质量。偏差指的是估计器的期望值与被估计参数的真实值之间的差异。一致性表示当样本大小增加时，估计器是否收敛到真实参数值，而效率则衡量估计器如何利用数据中可用的信息。此外，统计估计（统计估计）不仅限于描述性统计；它在推论统计中也发挥着重要作用。推论统计使研究人员能够根据样本数据得出关于总体的结论，这在医学、社会科学和经济学等领域特别有用。例如，临床试验通常依赖于统计估计（统计估计）来确定新药的有效性，通过比较治疗组和对照组之间的结果。总之，统计估计（统计估计）是数据分析世界中的一个重要工具，使研究人员能够根据有限的信息做出明智的决策。它的应用广泛而多样，影响着众多领域和行业。通过理解统计估计（统计估计）背后的原则和方法，个人和组织可以利用数据的力量推动进步和创新。