Course specification
Acronym 14PSPSO10
Study programme Psychology
Module
Type of study
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
ESPB 6.0 Status
Condition To attenting the course it is necessary for students to previously attend Introdaction to Statistics (14PSPSO04) course. Oblik uslovljenosti
The goal a) Introducing students: - to complex statistical concepts, constructs, and operators which are used in psychology studies - to complex statistical thinking necessary to understanding psychological phenomena and processes b) Train students: - to choose methods of statistical analyses - to use statistical programs for statistical data analyses - to understand multiple relations among variables as an assumption for studying multivariate analysis
The outcome At the end of this course, students are expected to be prepared: - to choose adequate statistical methods for research plots which are frequently used in statistical investigations with larger number of variables and/or multiple measures - to enter in computer data of typical psychological variables measurements and adjust them (by conversion or transformation) to the adequate model of statistical analysis - to carry out data analyses in the specified statistical programs - to interpret results of data analyses
Contents
Contents of lectures I Simple linear regression analysis; II Special problems in correlations among variables; III Multiple regression analysis; IV Univariate analysis of variance; V Multivariate analysis of variance, VI Analysis of variance with repeated measures; VII Explorative data analysis (visualization); VIII Selection of the methods for data analysis (statistical advisors)
Contents of exercises Conducting the statisical analyses using adequate statistical softwares and interpretation of the results
Literature
1. Petz, B. (2004). Basis of statistical methods for non mathematicians. Jastrebarsko: Naklada Slap. (pp. 299-354)
2. Guilford, J.P. (1968). Basis of pedagogy and psychology statistics. Beograd: Savremena administracija. (chapters 13-16, pp. 238-384)
3. Supplementary literature: StatSoft, Inc. (2007). Electronic Statistics Textbook. Tulsa, OK: StatSoft.
Number of hours per week during the semester/trimester/year
Lectures Exercises OTC Study and Research Other classes
2 2
Methods of teaching Lectures and exercises
Knowledge score (maximum points 100)
Pre obligations Points Final exam Points
Activites during lectures 10 Test paper 30
Practical lessons Oral examination 40
Projects
Colloquia 20
Seminars
Vrh strane