109年第1學期-1591 類別資料分析 課程資訊

評分方式

評分項目	配分比例	說明
Quizzes	40
Midterm	30
Final	30

教育目標

Introducing statistical models for categorical data used by statistical practitioners. 1. Introduction: Distributions and Inference for Categorical Data 2. Describing Contingency Tables 3. Inference for Contingency Tables 4. Introduction to Generalized Linear Models 5. Logistic Regression 6. Building,Checking, and Applying Logistic Regression Models 7. Loglinear Models for Contingency Tables In this semester, we may include some topics related to Data Mining such as Decision Trees, Bagging, Random Forests, and/or Boosting.

課程概述

Objective: Introducing statistical models for categorical data used by statistical researchers and practitioners. Prerequisites:(a) Elementary Statistics(b).At least one of the following packages(SAS, R/Splus, or SPSS). Contents : 1.Statistical inference for Two-way and Three-way Contigency tables under different assumptions. 2.Logit/Loglinear models and their extensions. 3.Generalized linear models with random effects for categorical responses. 4.Models checking and selection. 5.Asymptotic results and other advanced topics. Sofewares: 1.SAS: PPRC FREQ, GENMOD, LOGISTIC, CATMOD, and NLMIXED. 2.S-PLUS or R: chisq.test, glm, fisher. test, gee, and glmmPQL. 3.SPSS: crosstabs, logistic, and plum.

基本資料

選修課，學分數：3-0
上課時間：四/4,B,5[M107]
修課班級：統計系2-4
修課年級：年級以上
選課備註：大數據資料群組(105適用), 生物統計群組(106-109適用),曾修習統計學下期

參考書目

“Categorical Data Analysis” 3rd by Alan Agresti