Applied Statistical Analysis

Education facts

Code: SF2321

<p>This course aims towards students looking for a comprehensive understanding of the application of advanced statistical methods, primarily different regression techniques, both within the social sciences and for public and commercial analyses and reports. The overall aim is to teach theory-based empirical analysis through regression. An important part of the course is also the learning and use of a statistical data program (for example Stata and/or SPSS, R). The course starts with an introduction to the statistical software coupled with a recapitulation of more basic statistical procedures. The core of the course consists of two major parts. In the first part, the teaching is arranged in workshops. Each workshop is usually concentrated around one statistical technique and one hand-in assignment and consists of lectures and teacher led computer lab tutorials. You will learn the most commonly used regression techniques such as linear regression, categorical regression, multi level regression and time-series regression. The second part of the course is focused on an independent research paper in which you apply theory-based empirical analysis through statistical methods on a self-chosen research problem and data material. The course is preparatory for the master thesis work. After the course, you can apply explanatory models in the social sciences using different kinds of data material and different regression techniques.</p>

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.

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 Analysis

  University of Gothenburg

  Start date: 5 November 2024

  End date: 19 January 2025

  Pace of study: 100 %