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Software tools for statisticians
Tilastotieteilijän ohjelmistotyökaluja, spring 2009


Petri Koistinen


3 cu (Part I only) or 6 cu (Parts I and II).

Grading is either pass or fail. Arvosana-asteikko on hyväksytty/hylätty.


Advanced studies


  • Monday 10--12, room C128.
  • Thursday 10--12, room C128

The lectures will be held in English.

Voit kirjoittaa harjoitustehtävien ratkaisut (tai harjoitustöiden raportit) suomeksi.
Osan I materiaali on (pääpiirteissään) saatavilla myös suomeksi.

Easter holiday 9.-15.4.


This course consists of two parts, of which part one can be taken separately.

Part I is an introduction to using the R software.

R is a popular software environment for statistical computing and graphics.
R is free, open source, and has lots of documentation available online.
However, learning to use R on one's own is laborious, and therefore taking this course
can be useful.

The main topics in part I are

  • the R programming language
  • reading and writing data
  • R graphics
  • some statistical facilities of R

This part of the course can be passed by returning a sufficient number of solved exercises (to be announced later).

Part II

In part II we look at some other software useful for a statistician:

  • computer algebra systems (Maple)
  • report writing using LaTeX
  • the BUGS system for Bayesian analysis with the aid of MCMC methods

This part of the course can be passed by finishing practical work (harjoitustyö).

Part II cannot be taken separately, but only together with part I.


Part I of the course (Introduction to using R) does not have any formal prerequisites.
Some examples are, however, hard to follow if you do not have prior knowledge of statistics.

For part II you need to

  • understand (elementary) probability theory. E.g., Todennäköisyyslaskennan kurssi would be more than enough preparation.
  • have some understanding of Bayesian statistics in order to follow the BUGS examples.

Course material


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