This course focuses on standard nonparametric procedures useful for the analysis of experimental data. One-sample, two-sample, and multiple sample rank test and their power are covered. Goodness-of-fit tests, contingency table test are also covered. It also includes some modorn nonparametric techniques such as nonparametric distribution estimation, nonparametric regression, functional data analysises. Theories are are emphasized, such as U-statistics, power function, and asymptotic relative efficiency are introduced, but the applications are not completely neglected, some applications such as gene set enrichment analysis are also included.
Statistics
统计学主要利用概率论建立数学模型，收集所观察系统的数据， 进行量化的分析、总结，并进而进行推断和预测，为相关决策提供依据和参考。 它以数学作为基本工具，但又比数学更有实际用途，可以对生活中大量的无序的数据进行分析，找出它们的规律，从而为研究、决策提供基本的依据 。
