NTHU STAT 5230 - Discrete Analysis

Feb ~ Jun 2011


Shao-Wei Cheng

Institute of Statistics, National Tsing Hua University
(鄭少為, 清華大學/統計所)


Course outline

    The course will be given on the basis of 3 hours a week (Monday, 2:10~5:10 PM) in 綜合三館 room 840, two and half hours on lecture and half an hour on lab. The materials for teaching will be regularly posted on the course website (http://www.stat.nthu.edu.tw/~swcheng/Teaching/stat5230/). The format for the course will be similar to STAT 5410.

    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:



    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. 



Faraway, J.J. (2006), Extending the Linear Model with R, Chapman & Hall/CRC.


  1. Agresti, A. (2002), Categorical Data Analysis, 2nd edition, John Wiley & Son.
  2. Agresti, A. (2010), Analysis of Ordinal Categorical Data, 2nd edition, John Wiley & Son.

These books will be reserved in MATH library (綜合三館三樓).  



    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 handed in before the end 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, 1:00~2:00 PM. Questions by e-mail are also welcome: my e-mail address swcheng@stat.nthu.edu.tw.


    The information of teaching assistants is as follows:

name email address office hour location office hour
張明中 lovelink0131@gmail.com 綜合三館 room 820  Wednesday, 10-11 AM
馬光輝 smallmar123@gmail.com 綜合三館 room 633  Monday, 1-2 PM



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



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