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Probability and Statistics (Graduate School of ISEE)

2018 Winter, Friday: 8:40--10:10

datetitlekeywordsremark
--Oct. 5 No class
Univ. fes.
1Oct. 10 (Wed) Probability I Probability Space
Kolmogorov's axioms
exercise
slide
2Oct. 12 Probability II independence, Bayes' theorem
Discrete ditribution
exercise
slide
3Oct. 19 Probability III Continuous ditribution
Expectation, Moment, Variance, Covariance
exercise
slide
4Oct. 26 Probability IV Markov's inequality
Chebyshev's inequality
Law of large numbers
exercise
slide
5Nov. 2 Probability V Affine transformation
Central limit theorem
exercise
slide
6Nov. 9 Probability VI Distributions
7Nov. 16 Midterm Exam

8Nov. 22 (Thu) Statistics I Estimate Expectaion and Variance
Unbiased estimator
exercise
slide
9Nov. 30 Statistics II Maximum likelihood exercise
slide
10Dec. 7 Statistics III Interval estimation
Statistical test
exercise
slide
11Dec. 14 Statistics IV Linear regression exercise
slide
12Dec. 21 Statistics V Bayesian Inference
13Jan. 11 Probability/Statistics Advenced topic
--Jan. 18 No class
Preparation of National Center Test for University Admissions
14Jan. 25 Final Exam?
TBA
15Feb. 1


Office hour: Fri. 15:30--17:30


Books

  1. Christopher M. Bishop, Pattern Recognition and Machine Learning, Springer-Verlag, 2006.
  2. M. Mitzenmacher, E. Upfel, Probability and Computing: Randomized Algorithms and Probabilistic Analysis, Cambridge University Press, 2005.
[Šm—Ķ˜_(Probability)]
  1. •šŒĐģ‘Ĩ, Šm—Ķ‚ÆŠm—Ķ‰ß’ö, ƒVƒŠ[ƒYq‹ā—ZHŠw‚ĖŠî‘br 3, ’Đ‘q‘“X, 2002.
  2. G. Blom, D. Sandell, L. Holst (’˜), X^(–ó), Šm—Ķ˜_‚Ö‚æ‚Ī‚ą‚ŧ, ƒVƒ…ƒvƒŠƒ“ƒK[ƒtƒFƒAƒ‰[ƒN“Œ‹ž, 2005.
[“ŒvŠw(Statistics)]
  1. “ĄāV—m“ŋ, Šm—Ķ‚Æ“Œv, Œŧ‘ãŠî‘b”Šw 13, ’Đ‘q‘“X, 2006.
  2. “ú–{“ŒvŠw‰ï, “ŒvŠw (“ŒvŒŸ’č1‹‰‘Ήž), “Œ‹ž}‘, 2013.
  3. “Œ‹ž‘åŠw‹ģ—{Šw•”“ŒvŠw‹ģŽš•Ō, “ŒvŠw“ü–å, “Œ‹ž‘åŠwo”ʼnï, 1991.
  4. “Œ‹ž‘åŠw‹ģ—{Šw•”“ŒvŠw‹ģŽš•Ō, ŽĐ‘R‰ČŠw‚Ė“ŒvŠw, “Œ‹ž‘åŠwo”ʼnï, 1992.

Shuji Kijima
Dept. Info, ISEE, Kyushu University
E-mail: kijima@inf.kyushu-u.ac.jp
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