**Introduction to intelligent data analysis 2004/2005**

Lecturer: Ad Feelders.

For course schedule etc. look at the
official course page.

- Grades Practical Assignments here.
- No lecture on Thursday October 14, due to public transport strike!!
- Second Assignment has been posted (October 12).
- First assignment has been posted.

A lecture is denoted by its

In addition to the lectures, there are computer lab sessions in week 40, 42, 43 and 44 (wednesday 13.00-15.00 hours).

Lecture | Subject | Lecture Notes |
---|---|---|

36B | Introduction; method of least squares | Introduction;Section 4.1 and 4.2 |

37A | Statistical Inference: a refresher | Chapter 2, Section 3.1 |

37B | Statistical Inference: a refresher (vervolg) | Chapter 2, Section 3.1 |

38A | The simple linear regression model,distributions of the LS estimators | Section 4.3 (intro) and 4.3.1 |

38B | Linear regression: interval estimation, hypothesis testing | Section 4.3.2 |

39A | Linear regression: prediction, diagnosis | Section 4.3.3 and 4.6 |

39B | Multiple linear regression; matrix notation | Section 4.7, 4.8.1, 4.8.2 |

40A | Multiple linear regression; various topics | Section 4.8.3, 4.8.4, 4.9 |

40B | Multiple linear regression: model selection | Section 4.10 |

40C | Computer Lab with Splus | |

41A | Study Week: No Lectures | |

41B | Study Week: No Lectures | |

42A | Logistic regression I | Section 5.1, 5.2, 5.3 |

42B | Geen college in verband met OV-staking | |

42C | Computer Lab with Splus | |

43A | Logistic regression II | Section 5.4, 5.6 |

43B | Discriminant analysis I | Chapter 6 |

43C | Computer Lab with Splus | |

44A | Discriminant analysis II | Chapter 6 |

44B | Bayesian data analysis | Chapter 8 |

44C | Computer Lab with Splus | |

45A | Computer Intensive Methods | Chapter 7 |

45B | No Lecture |

- Lecture notes Introduction to intelligent data analysis.
- Solutions to exercises in the lecture notes.

The purpose of the computer lab is to develop some basic skills in the analysis
of data with the techniques discussed in this course.

In the computer lab we use the data analysis software S-Plus 6 for Windows. We scheduled four lab sessions, in weeks 40, 42, 43 and 44.

Assignments:

- First Assignment (Data for first assignment)
- Second Assignment (Data for second assignment)
- Third Assignment (Data for third assignment)

The course is graded through a written exam and three practical assignments. The practical assignments are graded: not satisfactory/satisfactory/good.

With grades P[1], P[2], and P[3] for the practical assignments and grade E for the written exam, the final grade F is computed as follows:

IF min(P[1],P[2],P[3]) = "not satisfactory" F := min(E, 4) ELSE F := E FOR i=1 TO 3 DO IF P[i]="good" F := F + 0.3 FI OD F := min(F,10) FI

F is rounded to the nearest half point if F >= 6.0. F is rounded to the nearest whole point if F <6.0. For CKI students F is always rounded to the nearest whole point.

It is not allowed to consult the course notes during the exam. You may however consult one A4 sheet of paper with a summary of the course material.

ad@cs.uu.nl