Course Info

Syllabus      Navigator: C. Andy Tsao  Office: SE A411.    Campus Tel: 3520

Lecture: Mon 1310--1600 @ SE A324.

Office Hours: Wed. 0910-1000, Thr. 1310-1500, Fri. 0910-1000 @ SE A411 or by appointment

Discussion Board: APLM @ Olympus

• Notes:   Week 1, Week2
• Midterm
• The midterm will be held on April 25 (Mon) 1310-1600 @ SE A324.
  
• The exam will cover the material covered in class and, roughly,  KNNL Ch 1; 2.1-2.4, 2.9, 2.10; 3.1-3.3, 3.8; Ch 5,  6.1-6.4; 8.1; 9.1-9.3.
• For ease exposition, so far we mainly focus the inferences such as the estimation of the fitted value, hypothesis testing and parameter estimation. Skip those sections related to confidence intervals for the moment. (We will get to that later.)
  
• Homework  (No late homework is allowed.)

  Date	Hand-in Problems	Due Date
  050308	KNNL: 1.2, 1.5, 1.9, 1.12, 1.13, 1.19, 1.28; 6.1, 6.2	050321
  050328	KNNL: 2.3, 2.5(except a), 2.17--22. 2.54  For AM grads or those look for challenges: 2.53, 2.55, 2.60, 2,61.	050418

  
  

R and softwares

• R ClassRoom R notes: Data Summary
• R Regression Sample Output, TVAD data set, anova r code,
  
• Experimenting with R, MASS 
• Document Reader: Ghostview, Acrobat Reader; Context (FREE Nice Editor for Programmers)
• Contributed Doc (From CRAN)
  

Reading (from JSE, etc) 

• Example for Stat Reports: Study Comparison ..., Body dimensions
• Data Sets: Forcasting computer usage, Major League Baseball Attendence
• Brief History of Linear Regression

Links

1. R website (original, mirror @ Academia Sinica), Local download: ftp://hagrid.am.ndhu.edu.tw
2. Data Sets of NKNW, refer to README.TXT for file names.
   
3. Rice Vlib in Stat , Stat Lib @ CMU, Data and Story Library, JM's Web (R doc, Research Stat help)

   Stat Club,   YesKno Cafe