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Lecturer(s)
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Lebeda Tomáš, doc. PhDr. Ph.D.
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Lysek Jakub, Mgr. et Mgr. Ph.D.
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Course content
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Introduction to IBM SPSS Statistics Descriptive Statistics Graphical representation of data Statistical hypothesis testing Correlation and regression and analysis Factor analysis The course is thematically divided into three sections. In the first section, the students will be introduced to the issue of statistical inference. Aspects of the probability theory and inferential statistics related to hypothesis testing are discussed (standrad normal distribution, confidence intervals, z-tests, chi-square tests). In the second section, the problems of the ordinary least squares regression models and logistic models are discussed (univariate and multivariate models. regression coefficients, R-square and other statistics necessary for interpretation). In the third section, the methodlogical assumptions behing the regression models are discussed because not maintatinig these assupmtions in practical research creates specific complications especially in social science research (especially assumptions of hetereoskedasticity and multicollinearity).
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Learning activities and teaching methods
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Lecture, Monologic Lecture(Interpretation, Training), Dialogic Lecture (Discussion, Dialog, Brainstorming), Demonstration
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Learning outcomes
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The goal of the course is to introduce students to the most widely used statistical research methods in political science. The students will understand a basic quantitave methods not only in political science research and they will be able to use these methods for their own research, especially their graduate theses.
The students are able to use quantitative methods, their interpretation and applications possibilities. The knowledge that the students will obtain throughout the course will allow them to create their own quantitative research design for the purposes of their own research, especially their graduate theses. The course is based on the acquiring of methodological skills in the area of analytical plitical science. The main acquired skills are therefore: 1. Individual analysis of quantitative datasets using advanced reserach methods. 2. The ability of statistical hypothesis testing in quantitative research. 3. User knowledge of the SPSS program.
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Prerequisites
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1. Knowledge of basic statistical operations and statistical hypothesis testing. 2. The ability to work with quantiative datasets.
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Assessment methods and criteria
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Written exam
Active participation in class, completion of practical task (25 %), final exam (75 %) The students have to achieve at least 75 % of overall rating.
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Recommended literature
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Field, A. (2009). Discovering statistics using SPSS. London: Sage.
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Hendl, J. (2012). Přehled statistických metod: analýza a metaanalýza dat. Praha: Portál.
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Johnson, Janet Buttolph, H. T. Reynolds. (2005). Political Science Research Methods. Washington D. C.: CQ Press.
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Pallant, Julie. (2011). SPSS Survival Manual. Crowns Nest: Allen & Unwin.
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