PSA_032 Mathematical and statistical methods for psychologists II

Faculty of Arts
Spring 2014
Extent and Intensity
1/2/0. 5 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. PhDr. Martin Jelínek, Ph.D. (lecturer)
Mgr. Helena Klimusová, Ph.D. (lecturer)
Mgr. Štěpán Veselý, Ph.D. (seminar tutor)
Guaranteed by
PhDr. Zdenka Stránská, Ph.D.
Department of Psychology – Faculty of Arts
Supplier department: Department of Psychology – Faculty of Arts
Timetable
Wed 8:20–9:05 zruseno D21, Wed 9:10–9:55 L11, Wed 10:00–10:45 L11, Wed 10:50–11:35 L11, Wed 11:40–12:25 L11
  • Timetable of Seminar Groups:
PSA_032/sk1: No timetable has been entered into IS.
PSA_032/sk2: No timetable has been entered into IS.
PSA_032/sk3: No timetable has been entered into IS.
PSA_032/sk4: No timetable has been entered into IS.
PSA_032/KS: No timetable has been entered into IS.
Prerequisites (in Czech)
PSA_004 Math and stat methods psych I && PSA_038 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
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 zpracování dat :analýza a metaanalýza dat. Vyd. 1. Praha: Portál, 2004, 583 s. ISBN 8071788201. 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. Vyd. 1. Praha: Svoboda, 1977, 351 s. URL info
  • DISMAN, Miroslav. Jak se vyrábí sociologická znalost : příručka pro uživatele. Praha: Karolinum, 1993, 374 stran. ISBN 8070668229. info
  • GREGOR, Miroslav, Svatka PŘADKOVÁ and Daniela SPĚŠNÁ. Statistika pro sociology. (Statistics for Sociology.). In Statistika pro sociology. Brno: Masarykova univerzita Brno, 1993. ISBN 80-210-0560-2. 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
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
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
The course is also listed under the following terms Autumn 1998, Spring 1999, Spring 2002, Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2015, Spring 2016, Spring 2017.
  • Enrolment Statistics (Spring 2014, recent)
  • Permalink: https://is.muni.cz/course/phil/spring2014/PSA_032