# Statistics 7301

## Schedule

This schedule is subject to revision. Students are expected to attend class meetings and to regularly check this page for updates to the schedule.

Date | Day | Lecture | Topic | Reading | Due |
---|---|---|---|---|---|

8/23 | W | 0 | Overview | Keener 3.1 | |

8/25 | F | 1 | Statistical models | Keener 3.1 | |

8/28 | M | 2 | Decision theory | Keener 3.1 | |

8/30 | W | 3 | Sufficiency | Keener 3.2–3.3 | |

9/1 | F | 4 | Sufficiency and partitions | ||

9/4 | M | No Class |
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9/6 | W | 5 | Minimal sufficiency | Keener 3.4 | HW1 |

9/8 | F | 6 | Exponential families | Keener 2 | |

9/11 | M | 7 | Exponential families | Keener 2 | |

9/13 | W | 8 | Exponential families | Keener 2 | HW2 |

9/15 | F | 9 | Exponential families | Keener 2 | |

9/18 | M | 10 | Convex loss functions | Keener 3.6 | |

9/20 | W | 10 | Convex losses (continued); Jensen’s inequality | Keener 3.6 | HW3 |

9/22 | F | 11 | Rao–Blackwell Theorem | Keener 3.5 | |

9/25 | M | Exam 1 (Lec 0-9, HW 1-3) |
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9/27 | W | 12 | Completeness and ancillarity | Keener 3.5 | |

9/29 | F | 13 | Unbiased estimation | Keener 4.1 | |

10/2 | M | 14 | Fisher Information | Keener 4.5–4.6 | |

10/4 | W | 15 | Information inequality | Keener 4.5–4.6 | |

10/6 | F | 16 | Method of moments | HW4 | |

10/9 | M | 17 | Maximum likelihood | ||

10/11 | W | 18 | MLE in exponential families | ||

19 | MLE in exponential families (online note) | ||||

10/13 | F | No Class |
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10/16 | M | 20 | Minimum contrast estimation | HW5 | |

10/18 | W | 21 | Overview of asymptotics | Keener 8.1 | |

10/20 | F | Exam 2 (Lec 10-19, HW4-5) |
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10/23 | M | 22 | Consistency of MLE in expo families | Keener 8.3 | |

10/25 | W | 23 | Delta method | Keener 8.2,8.5,8.6 | |

10/27 | F | 24 | Delta method | Keener 8.2,8.5,8.6 | |

10/30 | M | 25 | Consistency of M-estimators | Keener 9.1 | HW6 |

11/1 | W | 26 | Consistency of M-estimators (ULLN) | Keener 9.1 | |

11/3 | F | 26b | Consistency of M-estimators and MLE | Keener 9.2 | |

11/6 | M | 27 | Asymptotic normality of min contrast | HW7 | |

11/8 | W | 28 | Asymptotic normality and efficiency of MLE | Keener 9.3,9.7 | |

11/10 | F | No Class |
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11/13 | M | 30 | Nonparametric estimation and the empirical CDF | Wasserman 2.1 | HW8 |

11/15 | W | 31 | Statistical functionals | Wasserman 2.2 | |

11/17 | F | Exam 3 (Lec 20 - 28, HW6-8) |
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11/20 | M | 32 | Influence functions | Wasserman 2.3 | |

11/22 | W | No Class |
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11/24 | F | No Class |
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11/27 | M | 33 | Functional Delta method | Wasserman 2.3 | |

11/29 | W | 34 | Nonparametric density estimation | Wasserman 6.0 | HW9 |

12/1 | F | 35 | Asymptotic MISE of the histogram | Wasserman 6.2 | |

12/4 | M | 36 | Kernel density estimation | Wasserman 6.3 | |

12/6 | W | 37 | MISE bound for kernel density estimation | Wasserman 6.3 | HW10 |

12/11 | M | Final exam (10:00am – 11:45am) |