Text: Montgomery, D.C., Introduction to Statistical Quality Control, John Wiley & Sons (7th edition)
Chaps 1-5: Basic probability, statistics, and statistical process control (SPC)
Chap 6: Control chart for variables.
Chap 7: Control chart for attributes
Chap 9: Cumulative sum chart
Chap 10: Other SPCs
Chap 11: Multivariate SPC
Quiz1(by Jung-Huang), Quiz2 (by Yeu-Chieh), Quiz3 (by Riskiana), Quiz4 (by Zhong-Hsien)
Midterm (by Wei-Hsiang), Final (by Hsin-Ni),
=============================================================== Textbook: Emura T, Chen YH (2018), Analysis of Survival Data with Dependent Censoring, Copula-Based Approaches ( JSS Research Series in Statistics, Springer)
Basic survival analysis: Censoring, Kaplan-Meier estimator, Hazard function, log-rank test, Cox regression, Maximum likelihood estimation,
Survival analysis with copula: Copula, Dependent censoring, Copula-graphic estimator, Likelihood-based inference under dependent censoring, Gene selection, Survival prediction

HW#1 (by Jia-Han), HW#2(by Jia-Han), HW#3 (by Xingwei), HW#4 (by Jia-Han), HW#5, HW#6 (by Jia-Han) 
Midterm (by Jia-Han), Supplement1 (by Jiung Huang), Supplement2 (by Xingwei), Supplement 3 (by Jia-Han),  
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Textbook: An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani)
Contents: Linear regression, Ridge regression and Lasso, Spline, Prediction and cross validation, Tree, High-dimensional problem
HW#1 (by Ting-Yu), HW#2 revised by Yi-Shian, HW#3(revised by Yi-Fang), Class supplement (Chia-Rong, Bo-Kuan, Jia-Yu, Ting-Yu)
Midterm (by Yi-Fang), Q#1 ( by Yi-Shian), Q2(by revised by Xingwei), Midterm2 (by Yi-Shian), Final (ans. by Xingwei)
=============================================================== Textbook: Statistical Inference, 2nd edition, Casella & Berger, Duxbury (2002)
HW#1 (ans. by You-fang), HW#2 (by You-fang; by TA), HW#3 (by Yi-Hao by TA), HW#4 (by Hsiang-An), HW#5(by Zhong-Xian, by TA), HW#6(by You-fang, by TA), HW#7(by Yin-Chen)
Quiz#1 (ans. by Yin-Chen), Quiz#2 (ans. by Li-Hsieh), Midterm (by Chia-Yuh), Final   
Survival analysis, Techniques for censored and truncated data, 2nd ed. Klein and Moeschberger, Springer (2003)
Chap 2:  Basic distribution: Survival, hazard, and cause-specific hazard functions, Exponential, Weibull, and Pareto, lognormal distributions.
Chap 3: Censoring and Truncation; Right-censoring, Left-truncation, Likelihood function
Chap 4: Nonparametric Estimation: Kaplan-Meier/product limit estimator
Chap 7: Hypothesis Testing: Log-rank and Gehan’s tests for 2-samples, Trend test
Chap 8: Proportional Hazard Regression: Log-rank and Gehan’s tests for 2-samples
Chap 12: Parametric regression: Weibull regression, Log-normal regression
Chap 13: Multivariate survival analysis: Frailty model
Appendix A: Numerical techniques: Newton-Raphson algorithm
HW#1(ans. by 亞晟 ), HW#2(ans. by Wei Ting), HW#3(ans. by Wei Ting), Quiz#1(ans. by 雯婷),
Midterm (ans. by Bo-Hong),
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Text: Montgomery, D.C., Introduction to Statistical Quality Control, John Wiley & Sons (7th edition)
Chaps 1-5: Basic probability, statistics, and statistical process control (SPC)
Chap 6: Control chart for variables.
Chap 7: Control chart for attributes
Chap 9: Cumulative sum chart
Chap 10: Other SPCs
Chap 11: Multivariate SPC
HW#1 (ans. by Chia-Ru), HW#2 (ans. by 翌婷), HW#3 (ans. by Chia-Ru), Quiz#1 (ans. by Yu-Han),
Midterm (ans. by Yan-Kai), Final exam (ans. by Yan-Kai).   
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Textbook: The Elements of Statistical Learning, Second Edition (Hastile, Tibshirani, Friedman)
Contents:  Linear regression;  Ridge regression and Lasso;  Spline;
Prediction and cross validation;   High-dimensional problem

HW#1 (ans. by Yuan-Hsin), HW#2 (ans. by Yuan-Hsin), HW#3 (asn. by Yuan-Hsin), HW#4 (ans. by Wan-Chi), HW#5(ans. by Yuan-Hsin)  
Midterm#1 (ans. by Jian-Zhang), Midterm#2 (ans. by Wei-Chih), Quiz#1(ans. by Yuan-Hsin), Final exam(ans. by Bo Hong)

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Textbook: Testing Statistical Hypothesis, 3rd edition, Lehmann and Romano, Springer, 2005
Objective: We study the theory of hypothesis tests and confidence sets under a decision theoretic framework
Hypothesis Tests, Neyman-Pearson’s lemma, Monotone likelihood, UMP tests, Unbiased test, Goodness-of-fit tests, UMA confidence set
HW#1 (ans. by Jia-Han), HW#2 (ans. by Jia-Han), HW#3, HW#4 (ans. by Jia-Han), HW
Midterm#1 (ans. by Jia-Han), Final exam (ans. by Jia-Han)
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 Text: Statistical Models and Methods for Lifetime Data, 2nd Edition (2002) by JF Lawless
Chap 1:  Survival and hazard functions, Weibull, and lognormal, and other lifetime distributions.
Chap 2: Right-censoring, Left-truncation, Likelihood inference
Chap 3: Kaplan-Meier estimator, Estimation under right-censoring and left-truncation
Chaps 4, 5: Inference for parametric models
Chap 6: Cox proportional hazards model
Chaps 9, 11: Multivariate survival analysis
Quiz1 (ans. by Ya-Wen), Quiz 2 (ans. by Pei-Yuan), Medterm exam (ans. by Ya-Wen), Final exam (ans. by Yen-Wen)
HW1 (ans. by Chia-Ru), HW2 (ans. by Yen-Wen), HW3 (ans by Chia-Ru), HW4 (ans. by Yuan-Hsin) 
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Text: Theory of point estimation, Springer, 1998, 2nd ed.  E.L. Lehmann, George Casella
Chap 4: Average risk optimality
Bayes estimator (section 2 and 3), Empirical Bayes (section 6), Risk comparison (section 7)
Chap 5: Minimaxity and admissibility
Minimaxity and admissibility (section 1 and 2)
Chap 6: Asymptotic optimality
HW1(ans. by Jia-Han), HW2(ans. by Jia-Han), HW3(ans. by Jia-Han), HW4(asn. by Jia-Han), HW5 (ans. by Jia-Han), HW6 (ans. by Jia-Han)
Midterm Exam (ans. by Jia-Han), Final exam (ans. by Jia-Han) 

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Quality Control (品質管制),  2015 Fall, Tuesday, 14:00 - 16:50

Text: Montgomery, D.C., Statistical Quality Control (2009), International Student Version, Wiley & Sons(6th edition).

    Chap 3 (Basic probability distribution)
    Chap 4 (Range method, OC curve)
    Chap 5 (Average run length, etc.)
    Chap 6 (Control chart for continuous variable)
    Chap 7 (Control chart for discrete variable)
    Chap 9 (CUSUM control chart, etc.)
Quiz#1 (ans. by Ya-Wen) Average = 8.4 ; Quiz#2 (ans. by Wan-Chi), Average=6.1; Quiz#3 (ans. by Jia-Yu), Average=5.4; Quiz#4(ans. by Jia-Yu),
Midterm exam (ans. by 昱翔) Average=17.6; Final Exam (ans. by Meng-Chu)  Average=27.6
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Text: Theory of point estimation, Springer, 1998, 2nd ed.  E.L. Lehmann, George Casella
Chap 1: Preparation
Probability theory, exponential family, sufficiency & completeness, convergence, Rao-Blackwell theorem, Loss function
Chap 2: Unbiased estimation
UMVUE, Fisher information, Cramer-Rao lower bound
Chap 4: Average risk optimality
Bayes estimator, risk comparison, James-Stein (shrinkage) estimator
Report#1 (ans. by Jia-Han), Report#2(ans. by Jia-Han),  Report#3, Report#4(ans. by Jia-Han),  
HW#1 (ans. by Jia-Han), HW#2, HW#3, Midterm Exam (ans. by Jia-Han),  Q#1 (ans. by Jia-Han), Final Exam (ans. by Jia-Han).

========================================================================================================================= Textbook: Multivariate survival analysis and competing risks, Martin Crowder, Texts in Statistical Science, CRC Press (2012)
Part I: Univariate survival analysis; Survival and hazard functions;     Exponential and Weibull distributions
    Censoring, Interval censoring;      Maximum likelihood estimator (MLE)
Part II: Multivariate survival analysis
    Joint and marginal distribution;      Bivariate survival model (bivariate exponential),
    Frailty model;     Copula model
Part III: Competing risks
    Latent lifetimes;   Identifiability
HW#1 (ans. by Chi-Hung), HW#2 (ans. by Chi-Hung), HW#3 (ans. by Jia-Han), HW#4 (ans. by Jia-Han),
HW#5(ans. by Jia-Han), HW#6 (ans. by Jia-Han), HW#7(ans. by Jia-Han), HW#8 (ans. by Jia-Han)
Final Report (ans. by Chi-Hung)

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High-dimensional data analysis (多維度資料分析 ), 2015 Spring Thursday 9:00-11:50

Textbook: The Elements of Statistical Learning, Second Edition (Hastile, Tibshirani, Friedman)
Contents: Linear regression;  Ridge regression and Lasso;  Spline;
Prediction and cross validation;   High-dimensional problem

HW#1 (ans. by Ai-Chun), HW#2 (ans. by Ai-Chun),  HW#3(ans. by Ai-Chun), HW#4 (ans. by Ai-Chun), Optional HW (ans. by Ai-Chun), HW#5 (ans. by Ai-Chun),

HW#6 (ans. by Ai-Chun), HW#7 (ans. by Ai-Chun), Final Report (ans. by Ai-Chun).

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Quality Control (品質管制),  2014 Fall, Friday, 14:00 - 16:50

Text: Montgomery, D.C., Statistical Quality Control (2009), International Student Version, Wiley & Sons(>=6th edition)1.

1. Basic control chart ( Chap 3, 6, 7 )  -chart, R-chart, s-chart, MR-chart, np-chart, c-chart
2. Profile monitoring ( Chap 10 )
3. Multivariate chart ( Chap 11 ) Hotelling T2 chart, W-chart, |S|-chart, Regression adjustment
4. Basic experimental design ( Chap 13 ) Factorial design
Quiz#1(ans. by Ya-Ling), Average = 8.6 ;  Quiz #2(ans. by Hsiao-Han), Average=8,  Final exam (ans. by Yen-Wen)., Average=23.7

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Survival analysis, Techniques for censored and truncated data, 2nd ed. by Klein and Moeschberger, Springer (2003)
Chap 2:  Basic distribution (Exponential, Weibull, Lognormal distributions)
Chap 3: Censoring and Truncation (Right-censoring, Left-truncation, Likelihood function)
Chap 4: Estimation (Product-limit estimator)
Appendix: Numerical maximization (Newton-Raphson, Steepest ascent, Large sample theory)
HW#1: Exercise 2.1-2.20 (Klein & Moeschberger, p.57-61), ans. by Chi-Hung,
HW#2: Chapter 3, Exercise 3.7 (p.89);  Appendix A Example A.1 (p.444), ans. by Chi-Hung,
HW#3: Example A2 (Klein & Moeschberger, 2003; p.447), ans. by Chi-Hung
Final Report:  ans. by Chi-Hung 

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Evaluation: Final exam (30%), Mid-term exam (20%), Quiz (20%), Homework (20%) (in English)
In-class answer (10%)
Textbook: Statistical Inference, 2nd edition, Casella & Berger, Duxbury (2002) ====
Topic: Point estimation, Hypothesis testing, Interval estimation, Asymptotic evaluation.
HW1(ans. by Yi-Ping), Average =  9.4 / 10; HW2 (ans. by I Hsuan); Average = 4.6;  HW3 (ans. by Tian-Wen); Average = 9.5; HW4 (ans. by Hsiao-Han); Average = 2.2; HW5 
Q1 (ans. by Yen Ming), Average = 8.2  / 18;  Q2 (ans. by Chi-Hung); Average = 2.7 / 8   
Mid-term exam (ans. by Yen Ming), Average =  23 / 35; 
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Evaluation: Final exam (30%), Mid-term exam (20%), Quiz (20%), Homework (20%) (in English)
In-class answer (10%) (in English or Chinese)
Textbook: Statistical Inference, 2nd edition, Casella & Berger, Duxbury (2002)
HW1(ans. by Yi-Hsin), Average =  8 / 10;  HW2(ans. by Ya-Ling), Average = 9.2 / 10, HW3(ans. by Hsiao-Han), Average = 9.1 / 10, HW4(ans. by I-Hsuan), HW5(ans. by Yu-Chen), Average = 8.4.  
Q1(ans. by Pei-Ling), Average = 6.2 / 8;  Q2 (ans. by Ai-Chun), Average = 5.4 / 10;  Q3 (ans. by Chi-Hung), Average = 4.9,
Midterm exam (ans. by Hsiao-Han),  Average = 13 / 18;  Final exam (ans. by Wei-Ting), Average = 20.6,   

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Text: P. Billingsley (1995), Probability and Measure, 3rd Edition, Joho Wiley & Sons
We study mathematically complete development of probability, based on the theory of measure.
1.    Borel-Cantelli Theorem,   2. Fatou’s lemma, Monotone convergence theorem, Dominated convergence theorem
3.    Fubini’s Theorem;    4. The Kolmogorov inequality, Zero-one law;   5. Slutsky’s thorem; 6.    Law of large number
7.    Glivenko-Cantelli Lemmas;  8.    Central limit theorem;  9.    Radon-Nikodym theorem
10.    Martingale convergence theorem;   11.    Cramer-Wold Theorem
Evaluation: Presentation(20%), Homework(20%), Exam (60%)
HW1(ans. by She-Kai), HW2, HW3,  Midterm, Final exam,       

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Quality Control (品質管制),  2013 Spring, Friday, 14:00 - 16:50

Text: Montgomery, D.C., Statistical Quality Control (2009), International Student Version, Wiley & Sons(>=6th edition)1.

1.Basic control chart ( Chap 6, 7 ):  X_bar-chart, R-chart, MR-chart, p-chartFundamentals of statistics
2.Advanced control chart ( Chap 10 ): Charts for censored data, Profile monitoring
3.Multivariate chart ( Chap 11 ); Control ellipse, Hotelling T2 chart, W-chart, |S|-chart
Evaluation: Final exam (50%), Homework (20%),  Quiz(30%)
 HW1, HW2(ans. by Szu-Peng & Cian-Huei), HW3(ans. by Szu-Peng);  Quiz1(ans. by Shau Kai), Quiz2(ans. by Guo-Cheng).
NOTE: Their answers are not necessary correct !

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Textbook: Mathematical Statistics, 2nd edition, Jun Shao, Springer, 2003
Objective: We study the theory of hypothesis tests and confidence sets under a decision theoretic framework
Hypothesis Tests (Chapter 6); Neyman-Pearson’s lemma, Monotone likelihood, UMP & UMPU tests, Likelihood ratio test, Chi-square test, Wald’s test, Score test, Bayes test, Kolmogorov-Smirnov and Cramer-von Mises test
Confidence Sets (Chapter 7); Pivotal quantities, Inverting acceptance regions of tests, Bayesian credible sets, Prediction sets. UMA, UMAU, Asymptotic confidence sets, Confidence band
Evaluation: Final exam (40%), Mid-term exam (30%), Homework (30%)
HW1(ans. by HsinChieh ) HW2(ans. by HsinChieh), HW3, HW4, HW5, HW6:
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Text: Mathematical Statistics, 2nd edition, Jun Shao, Springer, 2003 (downloadable for NCU students).
1.Fundamentals of statistics
Exponential family, location-scale family, sufficiency & completeness, symbols O_p(1) & o_p(1), Slutsky‘s theorem , Delta method
2. Statistical decision theory
Loss function & Risk, MSE, 0-1 loss, Randomized decision, Admissibility, Rao-Blackwell theorem, Bayes risk
3. Unbiased estimation
UMVUE, Fisher information matrix, Cramer-Rao lower bound, linear models, LSE, BLUE
4. Estimation in parametric models
Bayes action, improper prior, Constant risk estimator, Minimaxity & admissibility, Simultaneous estimation, MLE, asymptotic optimality
Evaluation: Final exam (40%), Mid-term exam (30%), Homework (30%) HW#1, HW#2, HW#3, HW#4, HW#5, HW#6

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Office Hour: Wed, 13:30-15:00, or anytime ( contact by email )
Text: Mathematical Statistics, 2nd edition, Jun Shao, Springer, 2003 (downloadable for NCU students).
We study Mathematical Statistics from a decision theoretic point of view. The materials are:
(A) Testing
Likelihood ratio test, Chi-squared test, Score test, Bayes test, Goodness-of-fit test
(B) Confidence set
Pivotal quantity, acceptance region, Baysian credible set, Prediction set, UMA&UMAU sets,
Asymptotic confidence set
(C) Additional topics
Bayes estimators, Admissible & minimax estimators, Shrinkage estimators
Evaluation: Mid-term & Final exam (50pts), Homework(50pts) HW1, HW2, HW3
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Text: Statistical Process Control, Wetherill, G.B. & Brown, D.W., Chapman & Hall, 1991.
We study the method of statistical process control including the following materials:
1)Basic statistical inference, 2)Process capability, 3)Shewhart control charts, 4)Specification limits.
此課程所提供的統計製程管制方法將探討以下課題：
1)基礎統計推論, 2)製程能力, 3) Shewhart管制圖  4) 規格限制, 
其中，此課程將著重於理論及統計性質方法，而非工程工業方面的製程管制，且課程、講義皆為英語授課。
Final exam (38 points), Midterm exam (22 points), Homework#1 (25 points), Homework#2 (15 points) Answer by 蔡任勛 and 廖哲瑋
Presentation (55 points, presenters do not need to take both Midterm & Final exams) Presentation by周仕鎧: R qcc package
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Text: Mathematical Statistics, 2nd edition, Jun Shao, Springer, 2003 (downloadable for NCU students).
We study mathematical statistics from a decision theoretic point of view, including the following materials:
1)Measure theory & exponential family, 2)Decision theoretic framework, 3)Unbiased estimator, 4)MLE and Bays estimator, 5) Minimax, Admissible estimators, 6) Asymptotic theory, 7) UMP test 8) Likelihood ratio test other tests. Lecture is given in English.
此課程將由決策理論觀點探討數理統計，課題包含：1)      測度論及指數族；2)決策理論架構；3)不偏估計量；4)MLE及貝氐估計；
5)漸近理論；6)UMP檢定；7)概比度檢定及其他。
Final exam (40pt), Mid-term exam (30pt), Homework (30pt); HW1, HW2, HW3, HW4,