The course is the second part of a structured training in quantitative methods as used in the social sciences. In this course, students will learn the fundamentals of statistical inference and how it is applied. The course starts with the basic probability theories of distributions, then teaches the steps of statistical inference leading to estimation of parameters and hypothesis testing. The course will take students to the basic creation and interpretation of regression models. Students will have hands-on training through the use of the software program R.

Assessment

The classes will be a hands-on and practical immersion in quantitative methods. Each class will involve group or individual activities.

• Participation: 10%
• Preliminary steps for research paper (4 x 10%): 40%
• 1) research question and description of the research,
• 2) getting data, data description and cleaning data;
• 3) concept definitions and operationalization (dependent and independent variables) and variable descriptions (means, variance, etc);
• 4) model creation
• Exercises during the course (2 x 10%): 20%
• Final research paper: 30%

Competences, learning outcomes and teaching activities (PDF)