and two bigger projects (midterm and final) 60 %

The main component of the projects will be matlab, or Splus/R functions that perform certain analyses and produce graphics, these functions should be emailed to me and hardcopies sent to the TA's.

Turn in the complementary, explanatory part of your project, (this will be larger as we go on in the term), as a printed word-processed text, if you use formulas you might want to use LaTEXwhich is available on the leland machines to which you should have access.

**TA's ** Kris Jennings, `jennings@stat` and Ilana Belitskaya,
`ilana@stat.stanford.edu`

TA's office hours:

Kris Jennings: Monday, 2-3pm, Friday 1-2pm

Ilana Belitskaya: Tuesday 2-4pm

Address:`http://www-stat.stanford.edu/~susan/courses/stat208/`

Weekly consultation of the web site will be necessary and expected of all students.

Exploratory and Confirmatory Data Analysis |
week 1 | |

Motivating Examples |
week 1 | |

Easy Problems where other methods are available | ||

Hard Problems where this is the only game in town | ||

Computational Aspects |
week 2 | |

Monte Carlo Methods | ||

Balanced Bootstrap | ||

Complete Enumeration? | ||

Theoretical Aspects |
week 3 | |

The plugin principle | ||

Nonparametric and Parametric | ||

Other resampling Methods |
week 4 | |

The jackknife | ||

Cross Validation | ||

Monte Carlo Markov Chain | ||

Confidence Regions |
week 5 | |

Confidence Intervals | ||

Confidence Bands | ||

Multivariate bootstrap | ||

Bootstrapping for regression |
week 6 | |

Bootstrapping the rows | ||

Bootstrapping the residuals | ||

Multivariate regression and pitfalls | ||

Nonparametric Hypotheses Testing |
week 7 | |

With the bootstrap | ||

With permutations | ||

Better bootstraps |
week 8 | |

Jackknife-after-Bootstrap | ||

Bootstrap-after-Bootstrap | ||

Corrected Bootstrapping | ||

Theory:pivotal statistics | ||

Dependent Data |
week 9 | |

Block bootstrap for time series | ||

Spatial Data |