Statistical methods in the social sciences 1600-SZD-N-MSNS-SOC
During this workshop, we will go through the main sampling and analytical models used in social sciences: descriptive statistics, parametric and non-parametric tests, analysis of variance, linear and logistic regression, SEMs, and meta-analysis. As you may assume knowing the number of hours allotted, this workshop won’t be a typical course in statistics. Instead, it will be a statistics-reading course. The goal is to prepare the participants to understand and interpret statistics in academic writing, plus evaluate the analysis's reliability. We will also discuss how to describe quantitative outcomes. Hopefully, it will be useful for the usage of scientific literature and academic writing. Quickly reviewing the most popular models should also provide participants with knowledge of available tools.
Type of course
Course coordinators
Learning outcomes
Knowledge: Knows and understands:
WG_03 - methodology of scientific research
WK_03 - basic principles of knowledge transfer to the economic and social spheres as well as commercialisation of research results and the know-how related to them
Skills: Can:
UW_01 - use knowledge of various scientific or artistic disciplines to creatively identify, formulate and innovatively solve complex problems or perform research tasks, and specifically: define the purpose and subject of research and formulate a research hypothesis, develop and creatively use research methods, techniques and tools, draw conclusions from research results
UW_02 - make a critical analysis and evaluation of the results of scientific research, expert activity and other creative works and their contribution to the development of knowledge
Social competences: Is ready to:
KK_01 - critically evaluate the achievements of a given scientific or artistic discipline
KK_02 - critically evaluate own contribution to the development of a given scientific or artistic discipline
Assessment criteria
description of requirements related to participation in classes, including the
permitted number of explained absences;
Up to two absences are allowed.
principles for passing the classes and the subject (including resit session);
Active participation in at least six classes. For the resist session, the passing will be based on an oral exam.
methods for the verification of learning outcomes; oral credit
evaluation criteria
Knowledge in text discussed, active participation.
Practical placement
-
Bibliography
B. Tabachnick, L. Fidell Using Multivariate Statistics, 1996
A. Field Discovering Statistics Using SPSS 2005
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: