Course outline

    The course will include LECTURE and LAB. The lecture will be given on the basis of 3 hours a week (Monday, 1:20~3:10PM, and Tuesday, 11:10AM~12:00PM) in 綜合三館 room 834. The purposes of lab are for students to reinforce ideas learned in the lecture and to practice the skills of real-data analysis. Some video files will be used to teach and demonstrate the labs. Success in both lecture and lab are required to pass this course. The materials for teaching will be regularly posted on the course website (http://www.stat.nthu.edu.tw/~swcheng/Teaching/stat5230/index.php). The format for the course will be similar to STAT 5410 (Linear Model).

    The overall goal of the course is to provide students with practical knowledge of how to analyze categorical data, and how to interpret and understand the results of that analysis. The topics to be covered in the course include:

• Analysis of binary response
• Count regression
• Contingency tables
• Analysis of multinomial response
• Generalized linear models
  • Estimation and inference
  • Residuals and diagnostics
• Random- and mixed-effects models

Computing

    The software I will be using for the course is R (S-plus is similar and will also work but is not free). R is free with Windows and Unix versions. You can download your own copy from its website and use it wherever you find convenient. 

Textbooks

Faraway, J.J. (2016), Extending the Linear Model with R, 2nd edition, Chapman & Hall/CRC.

Reference

1. Faraway, J.J. (2006), Extending the Linear Model with R, 1st edition, Chapman & Hall/CRC.
2. Agresti, A. (2013), Categorical Data Analysis, 3rd edition, John Wiley & Son.
3. Agresti, A. (2012), Analysis of Ordinal Categorical Data, 2nd edition, John Wiley & Son.
4. McCullagh, P. and Nelder, J.A. (1989), Generalized Linear Models, 2nd edition, Chapman and Hall, London.

Assignment

    You are free to discuss the assignment questions with your classmates, but you must write up your answers individually. You CANNOT turn answers in as a group or simply reproduce a classmate's write up. Please DO NOT hand in your assignments in the format of including all details of R outputs. You should present your results in summary format only with R outputs that are required to support your answers. All homework must be submitted to our eLearn platform before the start of class on the day it is due.

Contact method and office hours

    My office is in 綜合三館 room 818 (phone extension: 33162). My office hour is scheduled on Tuesday, 10:00~11:00AM. Questions by e-mail are also welcome: my e-mail address swcheng@stat.nthu.edu.tw.

    The information of teaching assistants is as follows:

Grading

    Your grade will be determined by homework (30 %), a midterm (30 %), and a final exam (40 %). 

Prerequisites

    Knowledge of linear model (STAT 5410). Computing will be required, but no specific prior experience is necessary.