Date | Topics | References |
---|---|---|

Aug 30 | course overview supervised learning |
Course overview Supervised learning ISLR Ch 2†; Optimality of conditional expectation |

Sep 1 | bias-variance trade-off | Supervised learning ISLR Ch 2 Bias-variance decomposition |

Sep 8 | linear regression overview | Linear regression ISLR Ch 3 |

Sep 13 | interpreting regression coefficients | Linear regression ISLR Ch 3 |

Sep 15 | ordinary least squares (OLS) | Sep 15 Scribble OLS notes S.1‡ |

Sep 20 | linear model + Gaussian/normal error terms maximum likelihood under normality |
Sep 20 Scribble OLS notes S.2.1 |

Sep 22 | inference under normality | Sep 22 Scribble OLS notes S.2.2 |

Sep 27 | \(p\)-values classical linear model |
Sep 27 Scribble OLS notes S.3.1 |

Sep 29 | method of moments under exogeneity properties of OLS under exogeneity |
Sep 29 Scribble OLS notes S.3.2–3 |

Oct 4 | more properties of OLS under exogeneity | Oct 4 Scribble OLS notes S.3.3 |

Oct 6 | Gauss-Markov theorem | Oct 6 Scribble OLS notes S.3.3 |

Oct 11 | estimating the error variance \(t\)-statistic |
Oct 11 Scribble OLS notes S.3.3 |

Oct 13 | MIDTERM | |

Oct 20 | convergence of random variables (weak) laws of large numbers |
Oct 20 Scribble OLS notes S.B Convergence of random variables |

Oct 25 | central limit theorems convergence of functions of random variables |
Oct 25 Scribble OLS notes S.B |

Oct 27 | asymptotic properties of OLS | Oct 27 Scribble OLS notes S.4.1–2 |

Nov 1 | testing statistical hypotheses | Nov 1 video lecture OLS notes S.5.1 |

Nov 3 | \(z\)-test asymptotic power |
Nov 3 video lecture Nov 3 Scribble OLS notes S.5.2 |

Nov 8 | estimating \(\textrm{Avar}\big[\widehat{\beta}_n\big]\) | Nov 8 Scribble OLS notes S.5.3 Estimating \(\textrm{Avar}\big[\widehat{\beta}_n\big]\) |

Nov 10 | Wald test optimal linear prediction |
Nov 10 Scribble OLS notes S.5.4–5 |

Nov 15 | classification overview logistic regression |
Classification ISLR S.4.1–3 |

Nov 17 | generalized linear models linear discriminant analysis |
Nov 17 Scribble Classification ISLR S.4.4, S.4.6 |

Nov 22 | generative models for classification | Classification ISLR S.4.4–5 |

Nov 29 | (cross-)validation | Nov 29 video lecture Resampling methods ISLR S.5.1 |

Dec 1 | bootstrap | Resampling methods ISLR S.5.2 |

Dec 6, 8 | linear model selection and regularization | Linear model selection and regularization ISLR S.6 |

†ISLR refers to the textbook *Introduction to Statistical Learning*.

‡OLS notes refers to the notes on ordinary least squares.

Date | Topics | References |
---|---|---|

Sep 2 | R tutorial | ISLR S.2.3† |

Sep 9 | linear regression lab | ISLR S.3.6 |

Sep 16 | interpreting regression coefficients | ISLR S.3.6 |

Sep 23, Sep 30 | returns to scale in the US electric power industry | nerlove.XLS Returns to scale Nerlove (1957) - Returns to Scale in Electricity Supply |

Oct 7 | midterm review | Practice midterm Practice midterm solutions |

Oct 14 | NO LAB | |

Oct 21 | midterm debrief | |

Oct 28, Nov 4 | Testing the efficient market hypothesis | mishkin.XLS Efficient markets Mishkin (1991) - Is the Fisher effect real? |

Nov 11 | Chow test for structural change | |

Nov 18 | Classification methods lab | ISLR S.4.7 |

Dec 2 | Resampling methods lab | ISLR S.5.3 |

Dec 9 | final review | Practice final Practice final solutions |

Subject | References |
---|---|

Linear algebra | Linear algebra review and reference |

Probability | Review of probability theory The multivariate Gaussian distribution More on multivariate Gaussians |