Applied Statistical and Digital Methods

Education facts

Code: SC2320

The course consists of two modules: #### Module 1: Applied Statistical Analysis 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 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.

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.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Applied Statistical and Digital Methods

  University of Gothenburg

  Start date: 4 November 2026

  End date: 17 January 2027

  Pace of study: 100 %