STAT 211 Principles of Statistics
STAT 426 Methods in time series analysis
STAT 610 Distribution theory
STAT 614 Probability for Statistics
STAT 620 Asymptotic Statistics
| Date | Lecture Notes | Topics |
|---|---|---|
| Tue, Jan 18 | Lecture 1 | review of probability theory |
| Thu, Jan 20 | Lecture 2 | review of probability theory |
| Tue, Jan 25 | Lecture 3 | CLT, first-order delta method |
| Thu, Jan 27 | Lecture 4 | variance stabilizing transformation, second-order delta method |
| Tue, Feb 1 | Lecture 5 | moment estimators, Taylor expansions |
| Tue, Feb 8 | Lecture 6 | maximum likelihood estimation |
| Thu, Feb 10 | Lecture 7 | asymptotic normality, efficiency |
| Tue, Feb 15 | Lecture 8 | exponential family, ARE, super efficiency |
| Thu, Feb 17 | Lecture 9 | testing & confidence sets |
| Tue, Feb 22 | Lecture 10 | testing a subvector, definition of U-statistics |
| Thu, Feb 24 | Lecture 11 | examples of U-statistics, variance of U-statistics |
| Tue, Mar 1 | Lecture 12 | Hajek projection |
| Thu, Mar 3 | Lecture 13 | Hajek projection |
| Tue, Mar 8 | Lecture 14 | metric entropy, bracketing, uniform laws of large numbers |
| Thu, Mar 10 | Lecture 15 | Sub-Gaussianity, Hoeffding's inequality |
| Tue, Mar 22 | Lecture 16 | Symmetrization |
| Thu, Mar 24 | Lecture 17 | McDiarmid’s inequality |
| Tue, Mar 29 | Lecture 18 | Sub-Gaussian process, Dudley’s integral entropy |
| Thu, Mar 31 | Lecture 19 | Lipschitz functions, VC dimension |
| Tue, Apr 5 | Lecture 20 | VC dimension |
| Thu, Apr 7 | Lecture 21 | Convergence rate, Some concepts of convergence in distribution |
| Tue, Apr 12 | Lecture 22 | Asymptotically equicontinuous |
| Thu, Apr 14 | Lecture 23 | Donsker Class, Goodness of fit statistics |
| Tue, Apr 19 | Lecture 24 | Functional delta method |
| Thu, Apr 21 | Lecture 25 | Bootstrap, Gaussian sequence model |
| Tue, Apr 26 | Lecture 26 | Soft/hard-thresholding estimators, risk inflation |
| Thu, Apr 28 | Lecture 27 | Lasso consistency |