Applied Multivariate Statistical Analysis                                     

Course Info

• Syllabus     Navigator: C. Andy Tsao.   Office: SE A411.    Campus Tel: 3520
• Lectures: Mon 1310-1400, Thr 1310-1500@ SE A310
  
• Office Hours: Mon 1410-1500, Tue 1210-1300 @ SE A411 or by appointment
• Prerequisites: Statistics, Linear Algebra. Knowledge about regression or General/Generalized Linear Models will be helpful. 
• "Official" computing software: R (original, mirrors @ NTU, PU, Packages), Tinn-R (Editor for R), Rstudio
  
• References: 
• Hardle and Simar (2003). Applied Multivariate Statistical Analysis, Springer. (html @ xplore) (Textbook)
  
• Johnson and Wichern (2007). Applied Multivariate Statistical Analysis, 6th Edition. Pearson Education International.
• Midterm: April 17 (Thr) in class. 
• Project:  Project Guideline

Class slides, Homework, Data, Themes

Supplemental

• Applied Linear Models
  
• Presentation & Slides: Robin William's *RAP, Basic of Design (The Non-Designer's Design Book); Presentation Zen: Examples at Six Minute, in words, more; Technical Presentation: WikiHow, A Guide to Technical Presentations; NTU: 丙紳隨筆, 台大簡報課
• [鄉民的推導]等的分析──來自何小孟臉書(NEW)
• Attractiveness/Beauty ~ Averages?: Short Intro,  Average female faces of different countries, Demo@FaceResearch, BeautyCheck,  Papers: (Attractive Faces Are Only Average, Science of Beauty, 對稱最美@泛科學, FDA架構下多原型分類模型的改進)
• Google PageRank (NEW): How google finds your needle in the web's haystack, The Google Pagerank Algorithm
  and How It Works (and references therein)
• Factor Analysis links: Discussion, Poverty on Children Intelligence Development, IQ

Sample R codes and Freewares

• R bloggers
• xkcd.com (A webcomic of romance, sarcasm, math and language)