Official course description, subject to change:
Basic info last published 18/03-20

Digital Data Analysis

Course info
Language:
English
ECTS points:
7.5
Course code:
BADIDAA1KU
Participants max:
65
Offered to guest students:
yes
Offered to exchange students:
Offered as a single subject:
yes
Price (single subject):
10625 DKK (incl. vat)
Programme
Level:
Bachelor
Programme:
BSc in Digital Design and Interactive Technologies
Staff
Course manager
Associate Professor
Course semester
Semester
Efterår 2020
Start
24 August 2020
End
22 January 2021
Exam
Exam type
ordinær
Internal/External
intern censur
Grade Scale
7-trinsskala
Exam Language
GB
Abstract

The objective of the course is to learn how to analyze and visually quantitative digital data. The course is developed using the R language for data analysis and the Grammar of Graphics (as implemented in the R package ggplot) for data visualization.

Description

The course is important because quantitative data analysis is an essential part of user research and understanding user behavior and it is going to be more and more relevant with Digital Data analytics playing a central role in any type of business intelligence. In the larger context, students need a versatile toolbox for exploring users’ behavior, to develop a representative understanding of users’ practices. This toolbox needs to cover qualitative and quantitative methods for collecting and analyzing data about user behavior and practice. The course is divided into three sections: data analysis, data visualization, analysis of network data.  

The course will provide an introduction to the R programming language for statistical analysis. It will also introduce specific R packages for data visualization (ggplot) and for the analysis of network data (igraph).

The course will cover:

  1. Digital Data, types and format
  2. Introduction to R
  3. Data visualization with R/ggplot
  4. Datasets and data structures
  5. Graphs and network structures on social media data.

Formal prerequisites

This  course is a 3rd semester course on the BSc Digital Design and Interactive Technologies

Intended learning outcomes

After the course, the student should be able to:

  • describe the nature and types of digital data
  • discuss quantitative data analysis techniques and data visualization techniques
  • design and implement a research project on digital media data
  • use R to analyze and visualize quantitative data
  • discuss ethical implications of working with digital data
Ordinary exam
Exam type:
A: Written exam on premises, Internal (7-point scale)
Exam variation:
A11: Written exam on premises. Open book exam.