x !
Arkistoitu opetusohjelma 2017–2018
Selaat vanhentunutta opetusohjelmaa. Voimassa olevan opetusohjelman löydät täältä.
TAYJ024 Visualization of Quantitative Data 2 ECTS
Period I Period II Period III Period IV
Language of instruction
Type or level of studies
Postgraduate studies
Course unit descriptions in the curriculum
Yliopiston yhteiset tohtoriopinnot
Doctoral School

General description

Visualization of quantitative data when reporting and publishing findings

Course description:

It is commonly said that “a picture is worth a thousand words”. The same is true when reporting findings of an analysis of quantitative data. A proper visualization of the results might make the difference between the success and failure in telling a story or in publishing one’s findings. This course gives, first, a brief introduction to the R software and to D3 JavaScript library for manipulating documents based on data. Second, the course focuses on visualization of quantitative data which is of utmost importance when reporting and publishing findings. Examples and applications will be done for multivariate, temporal, spatial and text data. Examples used during the course will be based on the R software, and preliminary knowledge of this software is advisable but nor required. Participants can learn more about the R software prior to the course online at: http://www.uta.fi/cast/events/Ronline.html.

Goals: The course:

  • Introduces participants to the R environment and to D3
  • Introduces the participants to data exploration and data visualization
  • Provides a recent variety of techniques and strategies to visualize quantitative data

Place: Computer classroom Ml 50 Linna


Day 1: 3.11.2017

09.15-12.00   Introduction to R

12.00-13.00   Lunch break

13.00-16.00   Introduction to data exploration and data visualization: types of data and of databases; online databases; Visualization of multivariate data

Day 2: 10.11.2017

09.15-12.00   Visualization of temporal data and of spatial data; text visualization

12.00-13.00   lunch break

13.00-16.00 Introduction to D3; Real time big data applications

PLEASE NOTE: Attendance to BOTH days is required for the completion of the course.

Teacher: Paulo Canas Rodrigues

Pre-assignment: Please write a short (one A4) text stating:

1)    Your name & disciplinary background

2)    State your own motivation for participating on this course and what do you expect to learn.

DEADLINE for the pre-assignments to be announced.

In addition, participants will write a mini-assignment after the second meeting with a two weeks’ deadline.

Enrolment via NettiOpsu. Maximum number of students is 24. Selection method is draw. Students should check the selection result via NettiOpsu after the enrolment period.


Enrolment for University Studies

Enrolment time has expired


Rodrigues, Paolo, Teacher responsible
Pirjo Nikander, Other person


3-Nov-2017 – 10-Nov-2017