利用COVID-19疫苗功效数据进行单样本假设检验

Q3 Mathematics
Frank Wang
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引用次数: 1

摘要

2020年11月下旬,两家公司声称新开发的COVID-19疫苗的有效率为95%,媒体纷纷报道,但没有报道有关置信区间的信息。本文提出了一种利用媒体公布的辉瑞和Moderna制药公司公布的数字来教授假设检验概念和构建置信区间的方法,而不是采用双样本检验或更复杂的统计模型。我们使用基本oneproportion z检验分析数据的方法被设计成可访问只有一学期的学生基本统计课程我们将证明使用z分布作为一个近似置信区间的疗效率贝叶斯规则将被应用到相关的概率在疫苗组的志愿者感染COVID-19更间接的概率被COVID-19感染鉴于该人已接种疫苗©2021,National Numeracy Network保留所有权利
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using COVID-19 Vaccine Efficacy Data to Teach One-Sample Hypothesis Testing
In late November 2020, there was a flurry of media coverage of two companies’ claims of 95% efficacy rates of newly developed COVID-19 vaccines, but information about the confidence interval was not reported This paper presents a way of teaching the concept of hypothesis testing and the construction of confidence intervals using numbers announced by the drug makers Pfizer and Moderna publicized by the media Instead of a two-sample test or more complicated statistical models, we use the elementary oneproportion z-test to analyze the data The method is designed to be accessible for students who have only taken a one-semester elementary statistics course We will justify the use of a z-distribution as an approximation for the confidence interval of the efficacy rate Bayes’s rule will be applied to relate the probability of being in the vaccine group among the volunteers who were infected by COVID-19 to the more consequential probability of being infected by COVID-19 given that the person is vaccinated © 2021, National Numeracy Network All rights reserved
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来源期刊
Numeracy
Numeracy Mathematics-Mathematics (miscellaneous)
CiteScore
1.30
自引率
0.00%
发文量
13
审稿时长
12 weeks
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