Statistics 240: Nonparametric and Robust Methods. Lecture Notes
Lecture Notes (warning: rough drafts!)
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New notes—still rough!
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Previous notes:
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Chapter 1 (pdf)
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Mathematical preliminaries.
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Chapter 2 (html)
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Combinatorics, hypothesis testing,
parametric/non-parametric/robust methods.
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Chapter 3 (html)
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The randomization model.
Comparing two treatments in the randomization model.
Permutation test, Fisher's exact test.
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Chapter 4 (html)
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Ranks, Wilcoxon rank-sum test,
tied observations, Siegel-Tukey test, Smirnov test.
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Chapter 5 (html)
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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.
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Chapter 6 (html)
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Sign test for paired comparisons.
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Chapter 7 (html)
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Tests of independence, Spearman rank correlation,
run test
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Chapter 8 (pdf)
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Resampling methods, bootstrap,
jackknife, bootstrap and randomization tests, bootstrap confidence sets.
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Chapter 9 (pdf)
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Robustness and related topics,
resistance and breakdown point, the influence function, M-estimates,
estimates of scale, robust regression.
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Chapter 10 (pdf)
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Density estimation, kernel estimates,
nearest-neighbor estimates, wavelet shrinkage, inverse problems, methods for
inverse problems.