January 31, 2012

The Bootstrap (Advanced Data Analysis from an Elementary Point of View)

Quantifying uncertainty by looking at sampling distributions. The bootstrap principle: sampling distributions under a good estimate of the truth are close to the true sampling distributions. Parametric bootstrapping. Non-parametric bootstrapping. Many examples. When does the bootstrap fail?

Reading: Notes, chapter 5 (R for figures and examples; pareto.R; wealth.dat); R for in-class examples

Advanced Data Analysis from an Elementary Point of View

Posted by crshalizi at January 31, 2012 19:10 | permanent link

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