36-705
36-705 Intermediate Statistics, Fall 2017 - CMU Statistics
Course homepage: http://www.stat.cmu.edu/~siva/705/main.html
Review
Lecture Notes
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Lecture 1: (8/28) A very brief review
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Lecture 2: (8/30) Concentration inequalities
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Lecture 3: (9/1) Concentration inequalities
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Lecture 4: (9/6) Convergence
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Lecture 5: (9/8) Convergence
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Lecture 6: (9/11) Central limit theorem
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Lecture 7: (9/13) Uniform laws and empirical process theory
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Lecture 8: (9/15) Uniform laws and empirical process theory
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Lecture 9: (9/18) VC dimension
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Lecture 10: (9/20) Rademacher complexity
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Lecture 11: (9/25) Sufficiency
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Lecture 12: (9/27) Minimal Sufficiency and Rao-Blackwell
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Lecture 13: (9/29) Exponential Families
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Lecture 14: (10/2) Parametric Estimation
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Lecture 15: (10/4) Fisher Information and Decision Theory
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Lecture 16: (10/6) Decision Theory
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Lecture 17: (10/9) Minimax and Consistency of MLE
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Lecture 18: (10/11) Asymptotic Normality of MLE
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Lecture 19: (10/13) Hypothesis Testing
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Lecture 20: (10/16) More Hypothesis Testing
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Lecture 21: (10/18) LRT and Permutation Cut-offs
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Lecture 22: (10/23) Multiple Testing
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Lecture 23: (10/25) FDR and Confidence Sets
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Lecture 24: (10/29) Confidence Intervals
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Lecture 25: (11/1) Confidence Intervals and Causal Inference
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Lecture 26: (11/3) Causal Inference
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Lecture 27: (11/6) Non-parametric Regression
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Lecture 28: (11/8) High-dimensional Statistics
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Lecture 29: (11/13) More High-dimensional Statistics
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Lecture 30: (11/15) Bayesian Inference
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Lecture 31: (11/17) MCMC
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Lecture 32: (11/27) MCMC and Bootstrap
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Lecture 33: (11/29) Bootstrap and Model Selection
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Lecture 34: (12/1) Model Selection
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Lecture 35: (12/4) Distances between Distributions