Advanced Statistical Inference I & II

Note: Prediction is difficult, especially with respect to the future. As a result, listings of plans for classes, and of homework, are always subject to change. To be sure you're preparing the right homework, doing the right readings, etc.... check this page regularly. Often, homework assignments in particular will change --- either because of a small change to the assignment, or because I didn't get as far in class as I had planned and hence have to change (usually reduce) the assignment.

Note: Class meets Wednesday 1:00 - 2:50 and Friday 11:20-12:10 in 新數102 except where otherwise noted.

Instructor: 陳宏  舊數106   Email: hchen@math.ntu.edu.tw  Phone#: 3366-2846

      Office hours:  Wednesday 11-12/Friday 10:20-11:00, or by appointment

Teaching Assistant:  黃信雄           Email:  r93221018@ntu.edu.tw     Office hours:  Friday afternoon

成績評量方式

Sunday	Monday	Tuesday	Wednesday	Thursday	Friday	Saturday
			1 Class Equivalence Principle	2	3 Class Point Estimation	4
5	6 加退選	7	8  Class Point Estimation	9	10 Class  Point Estimation	11
12	13	14	15 Class Point Estimation	16	17 Class Point Estimation	18
19	20	21	22 Class Point Estimation	23	24Class Point Estimation  2 & 3	25
26	27	28	29  Class Asymptotic methods   4	30	31 Class Asymptotic methods 6

Sunday	Monday	Tuesday	Wednesday	Thursday	Friday	Saturday
						1
2	3	4	5民族掃墓節	6	7 Class  Asymptotic methods	8
9	10	11	12  Class  Asymptotic methods	13	14 Class  Asymptotic methods	15
16	17 期中考週	18	19 Class Asymptotic methods Overview	20	21 Class Asymptotic methods 3	22
23/30	24	25	26  Class  Test of hypothesis  4	27	28 Class Test of hypothesis  6	29

Sunday	Monday	Tuesday	Wednesday	Thursday	Friday	Saturday
	1	2	3  Class Test of hypothesis	4	5  Class  Test of hypothesis	6
7	8	9	10   Class Test of hypothesis	11	12 Class  Test of hypothesis	13
14	15	16	17 Class  Interval estimation	18	19  Class  Interval estimation	20
21	22	23	24 Class   linear model	25	26 Class  linear model B3	27
28	29	30	31  端午節

Sunday	Monday	Tuesday	Wednesday	Thursday	Friday	Saturday
				1	2  Class	3
4	5	6	7   Class	8	9  Class	10
11	12	13	14   Class	15	16  Class	17
18	19	20	21 期末考	22	23	24
25	26	27	28	29	30

Sunday	Monday	Tuesday	Wednesday	Thursday	Friday	Saturday
				1	2	3
4	5	6	7	8	9	10
11	12	13	14	15	16	17
18中秋節	19 學期 上課開始	20	21 Class Overview   Set Theory 1	22	23 Class Basics of Probability Theory 2 & 3	24
25	26	27	28  Class Conditional Probability and Independence 4	29	30 Class Random Variable 5 Density and Mass Functions 6

Some useful website:

1.  Optimization (convex and constrained optimization) See Lecture Notes 1, 2, 3, 10    

     at http://www.princeton.edu/~chiangm/class.html.

2.  Linear algebra: Professor Strang's Class 18.06 Linear Algebra Lecture Videos, Fall 1999

Software

• R programming language

  • （可由網路取得）at http://www.r-project.org/    –  

    Download at http://cran.cs.pu.edu.tw/ or http://cran.csie.ntu.edu.tw/

    Look for Precompiled Binary Distributions Windows (95 and later)

    Look for base.  Download   rw2011.exe

  • Basic Introduction : from Institute of Statistics, NCTU; look for Splus

  • Tutorial by Venables and Ripley

  • R manuals: They are downloadable as PDF files:
    • An Introduction to R: It gives an introduction to the language and how to use R for doing statistical analysis and graphics.
    • A draft of the R language definition: Document the language per se. They are useful to know when programming R functions.
    • Writing R Extensions : It covers how to create your own packages, write R help files, and the foreign language (C, C++, Fortran, ...) interfaces.
    • R Data Import/Export : Describe the import and export facilities available either in R itself or via packages which are available from CRAN.
    • R Installation and Administration 
    • The R Reference Index : It contains all help files of the R standard packages in printable form.
  • Quick look up: Rcard, Rguide.
    • R-tutorial

back to my home page.