Brief description of the course
Course is delivered in the form of lectures and practical classes.
The course consists of five parts; each part consists of four
lecture-training meetings of which all will take place in compute lab. Every part is arranged as series of lectures and computer classes. In the lecture part of the meetings, there will be given an introduction to the method and itsapplication in previous sociological studies; specialattention is paid to testing hypotheses and presenting and interpreting the results. As examples are used already published research articles. The training part ismeant for hands-on exercises about the
selected method on real data. As statistical software SPSS will be used.
In the first, introductory module the central focus will be on the basics of descriptive and inferential statistics, including topics such as uni- and bi-variate analysis and analysis of stability and of changes on the group and individual level. In the second part linear regression analysis will be introduced and discussed. The third part focuses on the basics of logistic regression analysis. Fourth part is devoted to multi-level regression analysis. Last, the fifths topic is factor analysis and its application.
Throughout the course, data mining and data preparation (creating new variables, etc.) for the analysis will be practiced.
In order to pass the course, four assignments (testing of a given research hypothesis by applying the method under study) have to be delivered.
Learning outcomes in the course
Upon completing the course the student:
- can implement of various statistical methods, present and interpret of results.