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Statistics 240: Nonparametric and Robust Methods. Lecture Notes

Lecture Notes (warning: rough drafts!)

New notes—still rough!
Previous notes:
Chapter 1 (pdf)
Mathematical preliminaries.
Chapter 2 (html)
Combinatorics, hypothesis testing, parametric/non-parametric/robust methods.
Chapter 3 (html)
The randomization model. Comparing two treatments in the randomization model. Permutation test, Fisher's exact test.
Chapter 4 (html)
Ranks, Wilcoxon rank-sum test, tied observations, Siegel-Tukey test, Smirnov test.
Chapter 5 (html)
The population model, power of the Wilcoxon rank-sum test, asymptotic power and comparison with Student't t Test, the normal scores test, estimating the shift d, confidence intervals for d, confidence intervals for quantiles from iid observations.
Chapter 6 (html)
Sign test for paired comparisons.
Chapter 7 (html)
Tests of independence, Spearman rank correlation, run test
Chapter 8 (pdf)
Resampling methods, bootstrap, jackknife, bootstrap and randomization tests, bootstrap confidence sets.
Chapter 9 (pdf)
Robustness and related topics, resistance and breakdown point, the influence function, M-estimates, estimates of scale, robust regression.
Chapter 10 (pdf)
Density estimation, kernel estimates, nearest-neighbor estimates, wavelet shrinkage, inverse problems, methods for inverse problems.