BI493广义线性模型课程教学大纲

广义线性模型课程教学大纲课程基本信息(Course Information)课程代码B1493*学时*学分322(Course Code)(Credit Hours)(Credits)*课程名称广义线性模型(Course Title)Generalized Linear Model*课程性质专业选修课(Course Type)Elective授课对象生物信息学、生物统计学或其他相关专业的本科学生(Target Audience）Undergraduates majored in bioinformatics/biostatistics*授课语言中英双语(Language of Instruction)Chinese +English*开课院系生命科学技术学院(School)School of Life Sciences and Biotechnology先修课程高等数学、线性代数、概率论、数理统计(Prerequisite)Calculus,Linear Algebra,Probability,StatisticsZuoheng Wang,Shuanggehttp://cbb.sjtu.edu.cn/course/授课教师课程网址Ma,Haiqun Lin (Yale),Huibi493(Instructor)(Course Webpage)Lu,Maoying Wu (SJTU)本课程将介绍自然科学和社会科学领域中针对定量和定性数据的广义线性回归分析方法和技术，例如针对定量数据的多元性性回归、ANOVA和ANCOVA,针*课程简介(Description)对二元分类数据的Logistic和Probit回归模型，针对计数数据的泊松回归模型和负二项回归模型，针对生存数据的分段指数模型等等。课程将在似然估计理论的框架下展开。作为一门专业课，本课程要求学生在掌握统计学理论的同时，能结合R语言等统计学语言，将学到的知识应用于本学科的数据分析中。This course will cover the classic statistical models for the analysis of quantitative andqualitative data encountered in natural and social science investigation,in the contextof likelihood theory.The statistical methods studied are the general linear models forquantitative responses (including multiple regression,ANOVA and ANCOVA),*课程简介(Description).binomial regression models for binary data(including logistic regression and probitmodels),models for count data (including Poisson regression and negative binomialmodels)and models for survival data(Piecewise exponential models fitted via Poissonregression).All of these techniques are covered as special cases of the GeneralizedLinear Model,which provides a central unifying statistical framework for the entirecourse.课程教学大钢(course syllabus)1.*学习目标(Learning似然估计理论与线性模型(Likelihood theory and linear models)(A5.2,A5.5.1)2.广义线性基础理论模型(Theory of generalized linear models)(A5.2,A5.5.l)Outcomes)3.二元与分类数据分析(Analysis of binary and categorical data)(A52,A5.5.l)