课程号：00137960
课程名称：统计思维
开课学期：春
学分： 3
先修课程：微积分、线性代数
基本目的：该课程提供一个较为系统、基础、前沿性的统计学概论，课程主要包含：统计学原理、统计推理、贝叶斯推理、统计模型和方法等。帮助学生学会如何实现或应用统计学方法和模型，并能掌握统计学所蕴含的数学机理，从而培养学生的统计分析与思维能力。
内容提要：
1 basic concepts and applications
1）likelihood 2）sufficiency 3）exponential family 4）frequentist 5）minimax theory
2 interpretations of uncertainty
3 statistical inference
1）inference, learning and information 2）parametric and nonparametric methods
3）the bootstrap 4）hypothesis testing and p-values
4 bayesian inference
1）the bayesian paradigm 2）parametric models 3）statistical decision theory
5 statistical models and methods
1）linear models 2）generalized linear models 3）generalized additive models
4）random effect modes 5）robust estimation 6）online learning
6 nonparametric statistics
1）the bootstrap and the jackknife 2）nonparametric regression 3）density estimation
7 advantaged topics
1）design and analysis of experiments 2）a/b test 3）empirical bayes
4）false discovery rate 5）large-scale hypothesis testing
教学方式：课堂讲授，每周3学时
教材与参考书：
1. cox, d. r.(2006).principles of statistical inference.cambridge university press.
2. efron, b. and hastie, t. (2016).computer age statistical inference: algorithms, evidence, and data science. cambridge university press.
3.rao, c. r. (1997). statistics and truth: putting chance to work (2nd ed.). world scientific.
4. stigler, s. m. (2016). the seven pillars of statistical wisdom.harvard university press.
学生成绩评定方法：平时作业50%，期末论文50%。
课程修订负责人：张志华 林伟
