Bayesian Statistics in Social Sciences
General data
Course ID: | 2500-PL-PS-SP15-16 |
Erasmus code / ISCED: |
14.4
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Course title: | Bayesian Statistics in Social Sciences |
Name in Polish: | Bayesian Statistics in Social Sciences |
Organizational unit: | Faculty of Psychology |
Course groups: | |
ECTS credit allocation (and other scores): |
2.00
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Language: | English |
Prerequisites (description): | (in Polish) Kryteria wejścia: Y2 Social Research Specialization |
Short description: |
The main goal of this course is to familiarize students with basics of Bayesian data analysis and its applications in social sciences. |
Learning outcomes: |
Upon completion of this course: students know basics of Bayesian data analysis and its theoretical underpinnings students know how to perform basic Bayesian analyses with R and brms students know potential applications of Bayesian models in social and behavioral sciences and are able use some of them in their own research |
Classes in period "Summer semester 2023/24" (in progress)
Time span: | 2024-02-19 - 2024-06-16 |
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MO TU W TH CW
FR |
Type of class: |
Classes, 15 hours
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Coordinators: | (unknown) | |
Group instructors: | Wiktor Soral | |
Students list: | (inaccessible to you) | |
Examination: |
Course -
Grading
Classes - Grading |
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Full description: |
Bayesian data analysis is an alternative to the classical (frequentist) approach to statistics, that deals directly with problems of uncertainty and probability in research problems. As pointed by many authors, flexibility in data modeling and easiness of interpretation of the results makes Bayesian data analysis a natural candidate to approach problems in modeling psychological processes. During this lab we will learn the basics of Bayesian approach to statistics. We will learn strengths of Bayesian alternatives to t-test, ANOVA, and regression analyses, and how to perform them using open-source software (R and brms). |
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Bibliography: |
Handbook for this course is: McElreath, R. (2016). Statistical rethinking: A Bayesian course with examples in R and Stan. Boca Raton: CRC Press. |
Copyright by University of Warsaw.