[Dept. of Computer Science]
Introduction to intelligent data analysis 2004/2005

Introduction to intelligent data analysis

Lecturer: Ad Feelders.
For course schedule etc. look at the official course page.

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Course Plan

There are two lectures each week. In the schedule below, we call them the A-lecture (tuesdays 13.00-15.00 hours) and the B-lecture (thursdays 11.00-13.00 hours).
A lecture is denoted by its weeknumber and A or B.
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  

Literature

Computer Lab

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:

Supplementary material for the computer lab:

Grading

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.

Written Exam

Last year's exams:

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