Analyzing the Score Data of Five Wine Samples from Two Groups of Experts Based on R Software
关键词: R软件； 专家评分； 两个正态总体均值及方差的假设检验； 均值的多重t检验； 系统聚类分析和距离判别分析； R Software； Specialists Evaluation； Hypothesis Testing of Two Normal Populations’ Mean and Variance； Multiple t Test of the Mean； Hierarchical Clustering Method and Distance Discriminant Analysis Method摘要:
Abstract: By using R software, we discuss the evaluations of five wine samples by two groups of specialists and the rationality of the evaluations. First of all, by using the hypothesis testing of two normal population means, we judge whether there are significant score differences between two groups of specialists. The test results show consistency of scores of two groups of specialists, and thus the evaluation result has certain fairness and rationality. Secondly, by using multiple t test of the mean, we can investigate the degree of differentiation of different samples by the specialists. Under the significance level of 0.05, the specialists can separate sample 1 from samples 2, 3, and 5, samples 2 and 4, samples 3 and 4. By ordering the levels of five samples from high to low, we find that the specialists can basically distinguish samples with levels with level difference by 1. But specialists do not effectively distinguish samples 1 and 4 (level difference 1.5), samples 3 and 5 (level difference 1). Then we use the hierarchical clustering method to classify five samples to three classes: excellent, good, and bad. Finally, by using the distance discriminant analysis method, the discriminant function is established based on the training sample, then by discrimination of the training sample, we get specialists’ misjudgment rate and accurate rate, and thus we can use the discriminant function to classify the new samples.
文章引用: 明 鹤 , 张应应 (2014) 基于R软件分析两组专家对五个葡萄酒样品的评分数据。 统计学与应用， 3， 133-140. doi: 10.12677/SA.2014.34018
 R Core Team (2014) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/
 薛毅, 陈丽萍 (2007) 统计建模与R软件. 清华大学出版社, 北京.
 杨虎, 刘琼荪, 钟波 (2004) 数理统计. 高等教育出版社, 北京.
 张应应, 魏毅 (2014) R函数实现正态总体均值、方差的区间估计及假设检验的设计. 统计与决策, 9, 74-77.
 Zhang, Y.Y. (2013) OneTwo-Samples: Deal with one and two (normal) samples. R package version 1.0-3. http://CRAN.R-project.org/package=OneTwoSamples
 王学民 (2009) 应用多元分析. 第3版, 上海财经大学出版社, 上海.
 方开泰 (1982) 有序样品的一些聚类方法. 应用数学学报, 1, 94-101.