## PSBA019 Statistics II

Faculty of Arts
Spring 2022
Extent and Intensity
1/2/0. 5 credit(s). Type of Completion: zk (examination).
Taught in person.
Teacher(s)
doc. PhDr. Martin Jelínek, Ph.D. (lecturer)
Mgr. Helena Klimusová, Ph.D. (lecturer)
doc. PhDr. Petr Květon, Ph.D. (lecturer)
Guaranteed by
doc. PhDr. Martin Jelínek, Ph.D.
Department of Psychology - Faculty of Arts
Contact Person: Jarmila Valchářová
Supplier department: Department of Psychology - Faculty of Arts
Timetable
Thu 9:00–9:50 B2.43
• Timetable of Seminar Groups:
PSBA019/01: Thu 10:00–10:50 B2.33, M. Jelínek, H. Klimusová
PSBA019/02: Thu 11:00–11:50 B2.33, M. Jelínek, H. Klimusová
Prerequisites
PSBA009 Methodology of Psychology I && PSBA012 Statistics I
PSBA012 Statistical methods I PSBA009 Methodology I
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course focuses on specific methods of statistical analysis including advanced multivariate techniques and statistical power concept. The lectures are complemented by examples of concrete analyses in the seminars. The subject follows the Statistical Methods I.
Learning outcomes
At the end of the course students should be able to: understand basic concepts of statistics and their application in psychological research; master basic and advanced data analysis procedures (bivariate analysis - crosstabulation, coefficients of association, correlation, partial correlation, linear regresion, factor analysis, cluster analysis, discriminant analysis, multidimensional scaling, structural modelling); understand the concept of statistical power and utilize it in the research design; read and understand the results of data analysis; present the data analysis results in a research report.
Syllabus
• Crosstabulation, Chi-square test, coeficients of association;
• Correlation, regression;
• Multivariate regression analysis;
• Statistical power, sample size, effect size;
• Statistical reports;
• Multivariate techniques: factor analysis;
• Multivariate techniques: cluster analysis;
• Multivariate techniques: MDS, discriminant analysis;
• Multivariate techniques: structural modelling;
• Item analysis, reliability;
• Aplication of methods of data analysis in psychological research.
Literature
• HENDL, Jan. Přehled statistických metod : analýza a metaanalýza dat. Páté, rozšířené vydán. Praha: Portál, 2015. 734 stran. ISBN 9788026209812. info
• FIELD, Andy P. Discovering statistics using IBM SPSS statistics : and sex and drugs and rock 'n' roll. 4th edition. Los Angeles: Sage, Texts, 2014. xxxvi, 915. ISBN 9789351500827. info
• URBÁNEK, Tomáš. Strukturální modelování v psychologii. 1st ed. Brno: Psychologický ústav AV ČR a Nakladatelství Pavel Křepela, 2000. 234 pp. ISBN 80-902653-4-0. info
• DISMAN, Miroslav. Jak se vyrábí sociologická znalost : příručka pro uživatele. 4. nezměněné vydání. Praha: Univerzita Karlova v Praze, nakladatelství Karolinum, 2011. 372 stran. ISBN 9788024619668. URL info
• HEALEY, Joseph F. Statistics: A Tool for Social Research. 3rd ed. Belmont, California: Wadsworth, Inc., 1993. 555 pp. ISBN 0-534-17742-5. info
• SWOBODA, Helmut. Moderní statistika. Edited by Ragnar Anton Kittil Frisch, Translated by Jaromír Císař. 1. vyd. Praha: Svoboda, 1977. 351 s. URL info
Teaching methods
Lectures, exercises in computer room, homework assignments.
Assessment methods
Exam: Two parts - written multiple-choice test and data analysis asignment (involves to plan and conduct data analysis and to present the results as in a research report). The points obtained from the exercises and homework assignments are also count in the final classification.
Language of instruction
Czech