Week |
Topics |

0 |
Course introduction, Introduction to Python |

1 |
Introduction to data analysis in Python |

2 |
Introduction to data analysis and visualization in Python |

3 |
Simple linear regression, parameter estimation |

4 |
Assessing the accuracy of the coefficient estimates |

5 |
Assessing the accuracy of the model, correlation |

6 |
Confidence/prediction intervals |

7 |
Multiple linear regression, model utility test, interactions |

8 |
Categorical predictors, model diagnostics & evaluation |

9 |
Overfitting, Cross validation, model selection |

10 |
Logistic regression, classifier evaluation |

11 |
Introduction to design of experiments, comparing experiments |

12 |
Experiments with a single factor, completely randomized design |

13 |
Blocking factors and common designs, randomized complete block design, Latin Squares design |