test, and multi-sample test are described on several examples of customer satisfaction studies on a sweet snack, teaching effectiveness, facilities services at an airport. It is useful to note that some other approaches to Likert scales description are also developed in Camparo and Camparo (2013) and Lipovetsky and Conklin (2018). Chapter 3 considers ranking for multivariate populations, known in various applied research, for example, in Chemistry, Engineering, Food Science, Biomedicine, Marketing Research, etc. For multiple response and predictor variables, the nonparametric combinations, or NPC inference is presented by several permutation tests, for instance, Anderson-Darling and multi-focus statistics, with application to food sensory analysis in wine, cream cheese, and bread quality. Chapter 4 focuses on the composite indicators used in performance monitoring (PM) for evaluation the satisfaction with public services, organizations, or products. Performance indicators (PI) are built as composition of several simple indicators, and used with NPC tests, which also include the satisfaction profiles. Implementation of this approach is shown on the students’ overall satisfaction with various organizational and teaching aspects of their university experience. Chapter 5 concludes that the parametric multivariate analysis of variance (MANOVA) should not be used for the rank-based inference by categorical responses but the NPC nonprone to the specifics of distributions should be applied. The chapter describes how a global null-hypothesis can be constructed, test statistics performed, sampling distributions and p-values estimated. Finally, working with the R-package npvm is described, with examples of its application and interpretation of the results. All examples are illustrated with multiple tables and color graphs, each chapter presents a list of the most recent publications. The book is interesting, innovative, and can serve to researchers interested in trying new techniques in customer satisfaction and other behavioral studies.

中文翻译：

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序列分析和相关方法：创新方法和应用

测试和多样本测试描述了几个关于甜食、教学效果、机场设施服务的客户满意度研究的例子。值得注意的是，Camparo 和 Camparo（2013 年）以及 Lipovetsky 和 ​​Conklin（2018 年）还开发了一些其他的李克特量表描述方法。第 3 章考虑了各种应用研究中已知的多变量总体的排名，例如化学、工程、食品科学、生物医学、营销研究等。对于多响应和预测变量，非参数组合或 NPC 推理由几个排列测试，例如，Anderson-Darling 和多焦点统计，适用于葡萄酒、奶油奶酪和面包质量的食品感官分析。第 4 章重点介绍绩效监测 (PM) 中用于评估对公共服务、组织或产品的满意度的综合指标。绩效指标 (PI) 由几个简单指标组成，并与 NPC 测试一起使用，其中还包括满意度概况。这种方法的实施体现在学生对其大学经历的各种组织和教学方面的总体满意度上。第 5 章得出结论，参数多元方差分析 (MANOVA) 不应用于通过分类响应进行基于等级的推理，而应应用不倾向于分布细节的 NPC。本章描述了如何构建全局零假设、执行测试统计、抽样分布和估计 p 值。最后，描述了使用 R 包 npvm，并附有其应用示例和结果解释。所有例子都用多个表格和彩色图表说明，每一章都列出了最近的出版物。这本书很有趣，具有创新性，可以为有兴趣尝试客户满意度和其他行为研究的新技术的研究人员提供服务。