TKHR23 - Quantitative Methods for HCI

Course Code:	TKHR23
Confirmed:	Jun 05, 2024
Valid From:	Aug 31, 2026

Education Cycle:	Second-cycle level
Disciplinary domain:	Technology
Subject group:	Computer Technology
Specialised in:	A1N Second cycle, has only first-cycle course/s as entry requirements
Main field of study:	Informatics

Intended Learning Outcomes (ILO)

On completion of the course the student shall:

Knowledge and understanding

demonstrate comprehension of quantitative studies by appropriate statistical terminology
display knowledge of the concepts of exploratory vs. confirmatory factor analysis
display knowledge of important concepts of multiple regression analysis

Skills and abilities

demonstrate the ability to explain the potentials and limitations of statistical methods for analysis of multivariate data
demonstrate the ability to identify which kind of multivariate statistical analysis is appropriate for a specific problem
demonstrate the ability to conduct multivariate statistical analyses with an appropriate statistical software
demonstrate the ability to assess the goodness-of-fit of a multivariate model

Judgement and approach

demonstrate the ability to assess the general usefulness/weaknesses of the statistical analyses treated in the course

Content

This course is an introductory course in quantitative methods available to master students. The goal of the course is to provide the master students with basic understanding of the role and potential of quantitative research methods, basic ability to understand and evaluate the merits and shortcomings of other researchers’ (quantitative) studies, basic ability to apply certain quantitative techniques in their own research.

The course includes the following elements:

Descriptive statistics + graphical analysis
Sampling and survey design
Factor analysis
Regression analysis
Approaches how to work with incomplete data

Type of instruction

Lectures and assignments.

Language of instruction is English.

Entry requirements

The applicant must hold the minimum of a bachelor’s degree (i.e the equivalent of 180 ECTS credits at an accredited university) with at least 90 credits in Informatics, Computer Engineering, Computer Science, or equivalent. Proof of English proficiency is required.

Examination and grades

The course is graded 5, 4, 3 or U.

Registration of examination:

Name of the Test	Value	Grading
Examination ¹	5 credits	5/4/3/U
Assignment	2.5 credits	G/U

¹Determines the final grade of the course, which is issued only when all course units have been passed.

Course literature

Please note that changes may be made to the reading list up until eight weeks before the start of the course.

Discovering Statistics Using IBM SPSS Statistics (Sixth Edition)
Andy Field
ISBN-13: 978-1529630008, ISBN-10: 1529630002

COURSE SYLLABUS