PSY252 Statistical data analysis II

Faculty of Social Studies
Autumn 2019
Extent and Intensity
0/2/0. 5 credit(s). Type of Completion: zk (examination).
Mgr. Jaroslav Gottfried (lecturer)
doc. Mgr. Stanislav Ježek, Ph.D. (lecturer)
Mgr. Karel Rečka (lecturer)
Guaranteed by
doc. Mgr. Stanislav Ježek, Ph.D.
Department of Psychology - Faculty of Social Studies
Contact Person: doc. Mgr. Stanislav Ježek, Ph.D.
Supplier department: Department of Psychology - Faculty of Social Studies
Timetable of Seminar Groups
PSY252/01: No timetable has been entered into IS. J. Gottfried
PSY252/02: No timetable has been entered into IS. S. Ježek
PSY252/03: No timetable has been entered into IS. K. Rečka
PSY117 Statistics
The course assumes the student has working knowledge of the elementary concepts of statistical description, inference, and probability. Ability to test simple hypotheses on means, proportions and correlations. In this sense the prerequisite of this course is FSS:PSYb1170 or an equivalent. Parallel with this course students take a research methods course (FSS:PSYb1120) that allows them to apply newly acquired knowledge and skills in a group research project.
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
there are 21 fields of study the course is directly associated with, display
Course objectives
The course is an introduction to applied statistical analysis using the IBM SPSS software. It introduces students to the most frequently used statistical models in psychology so that they are able to specify the model, estimate its parameters and interpret these parameters. Besides producing own analyses, the focus is also on the understanding of published analyses.
Learning outcomes
Students will be able to perform basic statistical analyses using the IBM SPSS software from data preparation to a written report on the results of the analyses in line with APA recommendations. In their analyses students will be able to make use of the most common models - multiple regression with continuous and categorical predictors and interaction of predictors, mediation linear model, logistic regression, multi-level regression, and factorial ANOVA. Students will be able to critically interpret the results.
  • 1. The analytic software environment of SPSS. 2. Statistical description using SPSS. 3. Testing means, proportions and correlations. 4. General analytical procedure, open science, missing data. 5. Multiple linear regression, mediation, moderation. 6. Logistic regression. 7. ANOVA, factorial ANOVA, ANCOVA. 8. Multilevel regression.
    required literature
  • Field, A.: Discovering statistics using SPSS, 5th Ed. Sage, 2018.
  • MORGAN, Susan E., Tom REICHERT and Tyler R. HARRISON. From numbers to words : reporting statistical results for the social sciences. Boston, MA: Allyn and Bacon, 2002. xiii, 125. ISBN 080133280X. info
  • Publication manual of the American Psychological Association. Sixth edition. Washington, DC: American Psychological Association, 2010. xviii, 272. ISBN 9781433805622. info
    recommended literature
  • GROTENHUIS, Manfred te and Chris VISSCHER. How to use SPSS syntax : an overview of common commands. Los Angeles: Sage, 2014. xvi, 127. ISBN 9781483333434. info
Teaching methods
lecture, seminar, online discussion, discussion of team projects
Assessment methods
6 team analyses/projects during the term, active particiaption in seminars, mid-term test, final test and practical exam
Language of instruction
Follow-Up Courses
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
Communication channels

Please use „PSYb2520“ in the subject of emails related to this course.

If you have questions about statistical theory or practice taught in this courses, please make maximum use of our pubic Facebook group „Statistika, metodologie, psychometrika“ There is no problem using English there. Lecturers read the group and response time there is shorter than to emails.

The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018.
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