样本不是总体

IF 1.2 Q2 EDUCATION & EDUCATIONAL RESEARCH
J. S. Allison, L. Santana, I. J. H. Visagie
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引用次数: 0

摘要

给定样本数据,如何计算参数值?虽然这个问题无法回答,但在统计学课堂上,当学生们了解样本和总体(或统计量和参数)之间的区别时,经常会遇到这个问题。统计教师也经常混淆这些概念。我们摘录了一份全国数学考试试卷,其中样本被误认为是总体,用来说明这种混淆以及样本变异及其与样本大小的联系。我们将讨论用于解释参数和统计量之间区别的两种方法。第一种是直观技术,将计算统计量的变异性与相应参数的固定值进行对比。之后,我们将讨论蒙特卡罗模拟技术,并解释这些方法可能带来的贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The sample is not the population
Given sample data, how do you calculate the value of a parameter? While this question is impossible to answer, it is frequently encountered in statistics classes when students are introduced to the distinction between a sample and a population (or between a statistic and a parameter). It is not uncommon for teachers of statistics to also confuse these concepts. An excerpt of a national mathematics examination paper, where a sample is mistaken for the population, is used to illustrate this confusion as well as sample variation and its link to sample size. We discuss two techniques that can be used to explain the difference between a parameter and a statistic. The first is a visual technique in which the variability in calculated statistics is contrasted to the fixed value of the corresponding parameter. Thereafter, we discuss Monte Carlo simulation techniques and explain the contribution that these methods may have.
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来源期刊
Teaching Statistics
Teaching Statistics EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
2.10
自引率
25.00%
发文量
31
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