107年第1學期-1761 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 |
選課分析
本課程名額為 70人，已有38 人選讀，尚餘名額32人。
登入後可進行最愛課程追蹤 [按此登入]。
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.
課程資訊
基本資料
選修課，學分數：3-0
上課時間：二/6,7,8[M120]
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(105-107適用), A群組(101-104適用),曾修習統計學下期
教師與教學助理
授課教師：蘇俊隆
大班TA或教學助理：尚無資料
Office HourOffice Hours : 二/9, 三/5,9, 四/8 ; [新管院M434]
授課大綱
授課大綱：開啟授課大綱(授課計畫表)
(開在新視窗)
參考書目
“Categorical Data Analysis” 3rd by Alan Agresti
開課紀錄
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