Applied Statistical and Digital Methods

The course is given as either a freestanding course or as part of a program at the Department of Sociology and Work Science. The course is a methods course at advanced level.

The course can be included in the following programs: 1) Master's program in Sociology (S2SOC) and 2) Master's program in Criminology (S2KRI)

Main field
Sociology
Criminology

Specialization
A1F, Advanced level, has second-cycle course/s as entry requirements

To be eligible for the course the student should have obtained a pass grade for a first cycle social sciences research methods course (at least 15 credits) and have obtained 15 credits from a second cycle core course in the social sciences, or the equivalent. English 6/English B or the equivalent level of an internationally recognized test, for example TOEFL, IELTS.

The course consists of two modules of 7.5 credits each.

Module 1: Applied Statistical Analysis (7.5 credits)

This module provides students with an in-depth understanding of study design and the application of statistical methods in social science research. Initially, the theoretical foundations of statistical inference, the relationship between research problem, research design and empirical material, and the importance of these factors for the choice of statistical analysis method are treated. Thereafter, the course focuses on the practical application of a selection of statistical methods, with the aim of being able to analyze and answer complex social science questions.

Module 2: Digital Methods in Social Sciences (7.5 credits)

This module introduces digital methods for analyzing social phenomena, with a particular focus on how digital data can be collected, processed and analyzed. The course combines theoretical perspectives with practical elements and provides students with both methodological understanding and technical skills. The content is divided into modules covering data collection and management, ethical and legal considerations, and the application of methods such as text analytics and social network analysis. A central theme throughout the module is how qualitative and quantitative methods can be combined to enrich analysis.

After passing the course the student should be able to:

Knowledge and understanding

• Reason about the epistemological foundations of some of the most central statistical and digital methods.
• Describe the conceptual and methodological foundations of statistical inference.
• Describe a selection of statistical and digital methods relevant to social science research, and explain the methodological conditions that justify their use.

Competence and skills

• Design scientific investigations and demonstrate an understanding of the relationship between research problems and chosen methods.
• Design and statistically test theoretically derived models.
• Apply advanced statistical and numerical methods with the support of appropriate software.
• Present, visualize, interpret and analyze results of statistical and numerical investigations.

Judgement and approach

• Critically analyze and evaluate research design and empirical results in social science research where statistical and digital methods are applied.
• Identify and critically evaluate research ethics issues in the social sciences.

Teaching is through lectures, teacher-led computer room exercises and oral presentations at mandatory seminars.

Language of instruction: English

The course is examined through written assignments, both in groups and individually, and oral presentation.

Restrictions regarding the use of generative AI are stated on the learning platform or equivalent. Students are obliged to inform themselves of the current rules for examining elements such as assignments, seminar assignments and exams in the current course.

If a student who has been failed twice for the same examination element wishes to change examiner before the next examination session, such a request is to be granted unless there are specific reasons to the contrary (Chapter 6 Section 22 HF).

If a student has received a certificate of disability study support from the University of Gothenburg with a recommendation of adapted examination and/or adapted forms of assessment, an examiner may decide, if this is consistent with the course’s intended learning outcomes and provided that no unreasonable resources would be needed, to grant the student adapted examination and/or adapted forms of assessment.

If a course has been discontinued or undergone major changes, the student must be offered at least two examination sessions in addition to ordinary examination sessions. These sessions are to be spread over a period of at least one year but no more than two years after the course has been discontinued/changed. The same applies to placement and internship (VFU) except that this is restricted to only one further examination session.

If a student has been notified that they fulfil the requirements for being a student at Riksidrottsuniversitetet (RIU student), to combine elite sports activities with studies, the examiner is entitled to decide on adaptation of examinations if this is done in accordance with the Local rules regarding RIU students at the University of Gothenburg.

The course is given one of the grades Pass with distinction (VG), Pass (G) and Fail (U). To get the grade Pass (G) you must pass both parts of the course. Pass with distinction (VG) requires a pass in both modules.

The results of and possible changes to the course will be shared with students who participated in the evaluation and students who are starting the course.