Fall 2020

  • Sociology

    Dissertation Tutorial: Sociology
    0 ECTS
    Lecturer(s)
    Course Type: core course
    Course Content

    Doctoral theses supervised by professors in the department of Sociology will be discussed.

    Please check with individual chairs for dates and times.

    BAS: Current Research Perspectives
    2 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: BAS
    Credits: 2
    Course Content

    The course "Current Research Perspectives" introduces first year doctoral students to the theoretically informed research approaches and substantive research fields that build the strongholds of social science research in Mannheim. A series of talks provides first year doctoral students with an overview of current debates and ongoing research in the fields of psychology, political science and sociology. CDSS faculty members will present an outline of their research fields, report on prime examples of their current research, and provide an outlook on potential topics for future research. Doctoral students will have the opportunity to discuss the short talks with the respective lecturer during the remaining discussion time.

    Assignment: Come-up with a research project idea that is informed theoretically or
    methodologically by insights from one or several CDSS faculty presentations (outside of
    your particular field) in this class. Write-up your idea and describe a potential research
    design in a short 3-page paper. The paper is due October 31st.

    Talk schedule

    Schedule
    Lecture
    21.09.20 - 12.10.20 Monday 10:15 - 13:30 Sowi Zoom 18
    BAS: Mathematics for Social Scientists
    2 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: BAS
    Credits: 2
    Course Content

    It is increasingly important for modern social scientists to have a level of mathematical literacy, as mathematical research methods such as statistics and formal modelling have entered the main stream. This course is intended to provide an introduction to mathematical logic and rigour, and to some fundamental mathematical concepts that form the foundation of the modern subject. The course covers introductory set and function theory, including analysis of functions, and includes sections on both probability and linear algebra, which together are the basis of data analysis.

    The exam is scheduled for 15 December from 10.15am

    Basic readings:

    • Knut Sydsaeter and Peter Hammond. 2008. Essential Mathematics for Economic Analysis. 3rd edition. Harlow: Prentice Hall


    Additional readings:

    • Alpha C. Chiang and Kevin Wainwright. 2005. Fundamental Methods of Mathematical Economics. 4th edition. Boston, Mass.: McGraw-Hill
    • Jeff Gill. 2006. Essential Mathematics for Political and Social Research. Cambridge: Cambridge University Press.
    • Malcolm Pemberton and Nicholas Rau. 2007. Mathematics for Economists. 2nd edition. Manchester: Manchester University Press.
    • Carl P. Simon and Lawrence E. Blume. 1994. Mathematics for Economists. New York: W. W. Norton & Company. McGraw-Hill.
    Schedule
    Lecture
    19.10.20 - 30.11.20 Monday 10:15 - 13:30 Sowi Zoom 18
    MET: Crafting Social Science Research
    6 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: MET
    Credits: 6
    Course Content

    All researchers face similar challenges with core issues of research design. A research design is a plan that specifies how you are going to carry out a research project and, particularly, how to use evidence to answer your research question. The goal of this course is to jump-start students with their dissertation proposal. This course should help students to see the trade-offs involved in choosing a particular research design in their research projects. Consequently students are expected to develop own ideas about potential research questions and actively participate in those seminar-style meetings that are organized within this lecture course.

    Course requirements & assessment

    Active participation, draft of dissertation proposal (graded)

    Schedule
    Workshop
    29.09.20 - 08.12.20 Tuesday 12:00 - 13:30 Sowi Zoom 18
    MET: Theory Building and Causal Inference
    6 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: MET
    Credits: 6
    Course Content

    Questions of cause and effect are at the heart of social science. And yet, establishing credible causal effects in empirical analyses is a difficult enterprise. This course will introduce some of the key conceptual and methodological approaches to tackle the causal inference problem: the potential outcomes model of causal inference, experimental designs, matching and regression, instrumental variables, regression discontinuity designs as well as difference-in-differences and fixed effects.

    Course requirements & assessment

    Active participation, term paper (graded)

    Schedule
    Workshop
    11.09.20 - 23.10.20 Friday 10:15 - 13:30 Sowi Zoom 14
    RES: CDSS Workshop: Sociology
    2 or 3 depending on applicable study regulations ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: RES
    Credits: 2 or 3 depending on applicable study regulations
    Course Content

    Participation is mandatory for first to third year CDSS Sociology students. Participation is recommended for later CDSS doctoral candidates, but to no credit.

    The goal of this course is to provide support and crucial feedback for CDSS doctoral candidates in sociology on their ongoing dissertation project. In this workshop CDSS students are expected to play two roles. They should provide feedback to their peers as well as present their own work in order to receive feedback.

    Schedule
    Workshop
    24.09.20 - 10.12.20 Thursday 11:00 - 12:00 Sowi Zoom 14
    RES: MZES A Colloquium "European Societies and their Integration"
    2 ECTS
    Course Type: core course
    Course Number: RES
    Credits: 2
    Course Content

    Please refer to the MZES webpages for dates and times.

    MET: Cross Sectional Data Analysis (Lecture + Tutorial)
    6 + 3 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 6 + 3
    Prerequisites

    Sound understanding of linear regression models (OLS), knowledge in linear algebra and calculus, and being familiar with the statistical package Stata.

    Course Content

    The main focus lies on the introduction to statistical models and estimators beyond linear regression useful to a social scientists. A good understanding of the classical linear regression model is a prerequisite and required for the further topics of the course. We will first discuss violations of the asymptotic properties of the linear regression model and ways to address these violations (heteroscedasticity, endogeneity, proxy variables, IV-estimator). The second part of the class is dedicated to rst the maximum likelihood estimator and second to generalized linear models (GLS) for binary choice decisions (Logit, Probit), ordinal dependent variables, and count data (Poisson, Negative Binomial). Classes will be accompanied by lab sessions to repeat and practice the topics from the classes. We will use the statistical package Stata.

    Course requirements & assessment

    •  Regular and active participation in the lab sessions.
    •  Presentation of a weekly exercise; you must hand in the slides of the presentation, the Stata syntax file and output of the respective exercise, and a short output interpretation.
    • written exam (graded, 90 min)

    Credits (9 ECTS for lecture & tutorial) will be awarded based on a passed written exam. Participation in the final exam is subject to having passed all course requirements as stated above.

     

    Schedule
    Lecture
    29.09.20 - 08.12.20 Tuesday 13:45 - 15:15 B 144 in A5, 6 or online Zoom B144
    Tutorial
    30.09.20 - 09.12.20 Wednesday 13:45 - 15:15 Sowi Zoom 08
    MET: Data and Measurement (Lecture + Tutorial)
    6 + 2 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 6 + 2
    Course Content

    Summary

    This course gives an overview of data used in political science and their measurement properties. At the beginning of the course we will focus on survey data and traditional statistics and move to data science approaches for big data towards the end of the course. Topics covered include the Total Survey Error (TSE) framework, operationalizing research questions, guidelines for writing survey questions, testing questions with cognitive interviews and eye-tracking, sampling, coverage, and nonresponse of survey and big data, and data analytics approaches in data science.

    Course assessment & requirements

    3 mock exams (pass/fail, Hausarbeit), active participation, term paper (graded)

    Schedule
    Lecture
    29.09.20 - 08.12.20 Tuesday 08:30 - 10:00 Sowi Zoom 01
    Tutorial
    29.09.20 - 08.12.20 Tuesday 10:15 - 11:45 Sowi Zoom 01
    MET: Multivariate Analyses (Theory + Lab Course)
    6 + 2 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 6 + 2
    Course Content

    The course introduces students to quantitative methods in political science. During the first half of the course, we will focus on linear regression models. The topics covered include discussions of the mathematical bases for such models, their estimation and interpretation, model assumptions and techniques for addressing violations of those assumptions, and topics related to model specification and functional forms. During the second half of the course, students will be introduced to likelihood as a theory of inference, including models for binary and count data.

    The main goals of this course are to develop sound critical judgment about quantitative studies of political problems, to understand the logic of statistical inference, to recognize and understand the basics of the linear regression model, to develop the skills necessary to work with datasets to perform basic quantitative analyses, and to provide a basis of knowledge for more advanced statistical methods.

    In the accompanying course "Tutorial Multivariate Analyses" students will develop the necessary expertise in using statistical software to conduct quantitative research in political science.

    Graded assignments include homeworks, a mid-term exam and data analysis projects.

    Schedule
    Lecture
    30.09.20 - 09.12.20 Wednesday 08:30 - 10:00 Sowi Zoom 11
    Tutorial
    30.09.20 - 09.12.20 Wednesday 15:30 - 17:00 Sowi Zoom 4
    01.10.20 - 10.12.20 Thursday 10:15 - 11:45 Sowi Zoom 18
    MET: Programming in R and beyond
    4 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 4
    Course Content

    The software R is a computer programming language designed for statistical analysis and graphics. The first part of the course deals with a basic introduction to R, i.e. data handling, basic statistical analyses, the creation of graphics, and linear modeling including test for specially designed hypotheses. In the second part we use R as a programming language for cognitive modeling. We will simulate data based on mathematical models of cognitive functions and analyze these data with maximum likelihood parameter estimation techniques. At the end, I will introduce some advanced techniques, for example the creation of statistical reports with R.
    The software package R is free and available on all major platforms (www.r-project.org). I also recommend the free and platform independent Software RStudio as a comfortable IDE for R (www.rstudio.com). A basic introduction to R can be found under:

    http://cran.r-project.org/doc/manuals/r-release/R-intro.pdf.

    Literature will be given during the course

    Academic assessment  - regular participation in the course; non-graded test

    Schedule
    Seminar
    biweekly 02.10.20 - 11.12.20 Friday 13:45 - 17:00 Sowi Zoom 02
    MET: Research Design (Lecture + Tutorial)
    6 + 3 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 6 + 3
    Course Content

    How do we know which research design fits best our research question? What requirements must be in place for good descriptive, causal and predictive inference? How do we estimate causal effects? How do we design and analyze experiments? Can we make causal claims from observational data? Researchers in the social sciences must be able to answer all of these questions.
    This course teaches the fundamental concepts behind the estimation of causal effects, including potential obstacles to causal inference. Real-world examples will be discussed in detail and students will apply the techniques learned with real datasets in R. Students will come away with an understanding of how to estimate causal effects in both randomized and observational settings, with a particular focus on the careful design of both types of studies.

    Tutorial

    In the practice sessions, students will learn how to implement causal inference methods in R. Students should bring their own laptop for the all practice sessions. Previous knowledge in R is not necessary although advantageous. Please make also sure to install R and R studio before the first practice session.

    Course requirements & assessment

    Homework, oral participation, presentation ,written exam (graded)

    Schedule
    Lecture
    01.10.20 - 10.12.20 Thursday 13:45 - 15:15 Sowi Zoom 10
    Tutorial
    01.10.20 - 10.12.20 Thursday 15:30 - 17:00 Sowi Zoom 14
    MET: SMiP - Research Training Group 'Statistical Modeling in Psychology' additional courses (CDSS only)
    Various ECTS
    Course Type: elective course
    Course Number: MET
    Credits: Various
    Course Content

    Further SMiP courses open to CDSS doctoral students are:

    Hands-on browser-based Experimentation Instructor: Felix Henninger, Date: 05. - 09.10.2020 (16:30 - 18:30) and 1 afternoon mid October, Location: remote (invitation via email for registered participants). PLUS: The instructor will share slides with audio explanations to study before the interactive online sessions.

    Introduction to R: Basics Instructor: Martin Schnuerch, Date: 29.10.2020 (10:00 - 18:00), Location: Mannheim or Heidelberg **

    Introduction to R: Advanced Instructor: Martin Schnuerch, Date: 30.10.2020 (09:00 - 17:00), Location: Mannheim or Heidelberg **

    Cognitive Modeling in R Instructor: Klaus Oberauer, Dates: 05.11. & 06.11.2020, Location: Mannheim or remote

    Even more power for SMiP: Basic and advanced statistical power analysis using G*Power and multiTree Instructor: Edgar Erdfelder, Date: 27.11.2020 (13:00 - 17:00), Location: remote (invitation via email for registered participants). PLUS: The instructor will share slides with audio explanations to study before the interactive online session.

    Evidence, Errors, and Belief: A Stroll through the Statistical Inference Maze Instructor: Martin Schnuerch, Dates: 10.12. and 11.12.2020 (14:00 - 18:00), Location: remote, invitation via email for registered participants. PLUS: The instructor will share prep materials to study before the interactive online sessions.

    Improving your statistical questions Instructor: Daniel Lakens, Dates: 21.01. & 22.01.2021, Location: Freiburg or remote

    Registration for SMiP courses must be done directly via Annette Förster, SMiP Administration Assistant.

    Further details and registration.

    MET: SMiP Foundations of Statistical Modeling (CDSS only)
    6 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 6
    Course Content

    This course gives an advanced overview of standard multivariate methods and current developments in multivariate modeling. The topics include general and generalized linear models, structural equation models, multilevel modeling and specific models for the analysis of time-related effects. In the morning sessions, we will provide the formal foundations and theoretical background of the model classes for continuous and discrete observations. The afternoon sessions focus on empirical applications and hands-on exercises in data analysis.
    The goals are to bring the PhD candidates to a common level of statistical knowledge and data analytic skills and to set the stage for the more specialized topics in the Foundations 2 course and workshops in the following semesters.

    Dates

    Foundations 1 (Instructor: Thorsten Meiser, Assignment: Exercises in statistical modeling and analysis)

    15.10. (09:30 - 17:30) and 16.10.2020 (09:00 - 17:00), Location: Mannheim or Heidelberg

    19.11. (14:00 - 17:00) and 20.11.2020 (14:00 - 17:00), Location: remote, invitation via email for registered participants. PLUS: The instructor will share prep materials to study before the interactive online sessions.

    2 days mid December / beginning of January, Location: Mannheim

    Further details can be found on the web page of the RTG 'Statistical Modeling in Psychology'

    MET/POL: Game Theory (Theory + Tutorial)
    6 + 2 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET/POL
    Credits: 6 + 2
    Course Content

    The objective of this course is to provide students with the basics of formal modeling in political science. The course has some breadth in coverage in the sense that it provides a graduate-level introduction and overview to di erent areas in game theory. It is also narrow in the sense that the emphasis is not on application and model testing but getting trained in reading and writing down formal models. At the conceptual level the course will cover the following topics: normal form games, Nash equilibria, extensive form games, subgame perfect equilibria, repeated games, bargaining, games with incomplete and imperfect information, Bayesian perfect equilibria, signaling games, preferences and individual choices, basics of decision theory and social choice. At the substantial level, we will use these concepts to study, as examples, candidate competition, political lobbying, and war and deterrence.

    Literature
    tba

    Assessment: To pass the course you need an average grade of 4.0 or better in the midterm and the final exam. Final grading of the course will then be based on three components: assignments (20%), mid-term exam (30%), final exam (50%).

    Additional course dates on Tuesday from 3.30 to 5pm (Room: Sowi Zoom 10):

    29 September

    6 October

    13 October

    24 November

    7 December

    Tutorial

    This tutorial accompanies the graduate-level introductory lecture in game theory. Its main objective is to practice solution concepts for static and dynamic games of complete and incomplete information.
    The contents are centered on the material covered in the lecture. Thus, the following key areas will be discussed: preferences and individual choices, decision theory, normal form games, Nash equilibria, extensive form games, subgame perfect equilibria, repeated games, bargaining, games with incomplete and imperfect information, Bayesian perfect equilibria, signaling games. At the substantial level, we will use these concepts to study, for instance, candidate competition, political lobbying, and war and deterrence. Students are required to submit four problem sets. Moreover, it is essential for students to prepare thoroughly for all sessions using online tutorials. Active participation in class discussions is expected.

    Course requirements: Four problem sets.

    Schedule
    Lecture
    Additonal slots on Tuesday from 3.30 to 5pm, dates listed under course content 28.09.20 - 07.12.20 Monday 13:45 - 15:15 Sowi Zoom Room 8
    Tutorial
    02.10.20 - 11.12.20 Friday 08:30 - 10:00 Sowi Zoom 08
    MET/PSY: Theories and Methods in Social Psychology
    4 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET/PSY
    Credits: 4
    Course Content

    This seminar has a particular focus on research activities in social psychology. Unlike seminars that concentrate on one core thematic topic, this seminar will address a selected variety of different research topics in current social psychology. In each seminar session we will have a presentation either by participating Ph.D. students or by members of the social psychology group. Each presentation will address a current research topic in social psychology. The seminar provides the opportunity to actively discuss methodological, theoretical, and applied implications of the presented research. A particular focus will rest on the discussion of general methodological aspects.

    Literature: Will be announced in the seminar

    Examination (graded): Awarded for (a) active participation in the seminar discussions, (b) own presentation, and (c) homework. Grades are based on the homework (essay).

    Schedule
    Seminar
    01.10.20 - 10.12.20 Thursday 13:45 - 15:15 Sowi Zoom 03
    SOC: Advanced Topics in Migration & Education: Educational Inequalities in Europe
    6 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: SOC
    Credits: 6
    Course Content

    For long, education has been seen as a “giant sorting machine” for life chances in industrialized societies (Dunlop et al. 1975). This truism has been holding for decades. In light of technological changes and the expansion of knowledge-based tasks, education might increase its importance even more. Yet, educational opportunities are unevenly distributed. Social origin (parental class, income, education, wealth as well as (epi-)genetic dispositions), ethnic background, and gender affect chances of educational transitions and educational attainment. Inequality of educational opportunities also vary by country and across time. In the seminar on educational inequalities in Europe, we discuss classic and more recent theories of educational inequalities, different trends over time and cross-national variation in Europe, and we focus on selected dimensions of educational inequalities.

    Course requirements & assessment

    Regular small assignments (developing research questions based on the readings); compulsory attendance; participating in active discussion.

    Written term paper (max. 5000 words, graded), deadline: Jan 31, 2021

    Schedule
    Seminar
    not on 21 Oct and 11 & 25 Nov 30.09.20 - 02.12.20 Wednesday 08:30 - 11:45 Sowi Zoom 18
    SOC: Advanced Topics in Migration & Education: Educational Inequalities in Europe
    6 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: SOC
    Credits: 6
    Course Content

    For long, education has been seen as a “giant sorting machine” for life chances in industrialized societies (Dunlop et al. 1975). This truism has been holding for decades. In light of technological changes and the expansion of knowledge-based tasks, education might increase its importance even more. Yet, educational opportunities are unevenly distributed. Social origin (parental class, income, education, wealth as well as (epi-)genetic dispositions), ethnic background, and gender affect chances of educational transitions and educational attainment. Inequality of educational opportunities also vary by country and across time. In the seminar on educational inequalities in Europe, we discuss classic and more recent theories of educational inequalities, different trends over time and cross-national variation in Europe, and we focus on selected dimensions of educational inequalities.

    Course requirements & assessment

    Regular small assignments (developing research questions based on the readings); compulsory attendance; participating in active discussion.

    Written term paper (max. 5000 words, graded), deadline: Jan 31, 2021

    Schedule
    Seminar
    not on 21 Oct and 11 & 25 Nov 30.09.20 - 02.12.20 Wednesday 08:30 - 11:45 Sowi Zoom 18
    SOC: Organizational Theory
    6 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: SOC
    Credits: 6
    Course Content

    This advanced seminar will explore classic and recent social science research that seeks to explain variation in organizational behavior and development. We will consider a variety of research questions that tap into both formal and informal ways of organizing: what kinds of institutions are necessary to make economic organization work? Where do such institutions come from? Why do we observe very different outcomes across contexts even though they share the same market-supporting institutions? Why do some organizations survive even though they face the most unfavorable environments? How do conditions at the time of an organization's birth shape its development? To address these and further questions, we will rely both on recent theoretical advances and on empirical studies in a various settings.

    Course requirements & assessment

    • Presentation
    • Active participation
    • Term paper (graded)
    Schedule
    Seminar
    01.10.20 - 10.12.20 Thursday 10:15 - 11:45 Sowi Zoom 02
    SOC: Questionnaires for Cross Cultural Surveys
    6 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: SOC
    Credits: 6
    Course Content

    This course presents an overview of major issues in cross-cultural survey research. It covers the following topics:

    • Cross-cultural requirements during questionnaire development to ensure comparability
    • Informed decisions about how to measure (background) variables to ensure comparability
    • Best practice in carrying out questionnaire translation and assessment
    • Performing invariance tests (using Stata or R) and search for reasons for lacking equivalence by using probing techniques

    The contents of the course is not only relevant for those who want to conduct cross-cultural surveys but also for those who work with intercultural comparative survey data.

    Course requirements & assessment

    • Active participation
    • Oral presentation
    • Seminar paper (graded)
    Schedule
    Seminar
    28.10.20 - 09.12.20 Wednesday 13:45 - 17:00 Sowi Zoom 14
    SOC: Sociological Research on Corona/Covid-19
    6 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: SOC
    Credits: 6
    Course Content

    The course deals with social science research on the social and policy consequences of the Corona crisis. One focus willl be on the results of the Mannheim Corona Study (https://www.uni-mannheim.de/en/gip/corona-study/)

    Course requirements & assessment

    Active participation (obligatory attendance: at least 80% percent = requirement fulfilled; 80% to 60% = text summaries as compensation; less than 60% = failed); lecture and discussion of the texts, written answers to questions about the texts; short presentation.

    Term paper (about 15 pages, graded). Deadline: 15 January 2021

    Schedule
    Seminar
    30.09.20 - 09.12.20 Wednesday 12:00 - 13:30 Sowi Zoom 07
  • Political Science

    Dissertation Tutorial: Political Science
    0 ECTS
    Lecturer(s)
    Course Type: core course
    Course Content

    Doctoral theses supervised by professors in the department of Political Science will be discussed.

    Please check with individual chairs for dates and times.

    BAS: Current Research Perspectives
    2 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: BAS
    Credits: 2
    Course Content

    The course "Current Research Perspectives" introduces first year doctoral students to the theoretically informed research approaches and substantive research fields that build the strongholds of social science research in Mannheim. A series of talks provides first year doctoral students with an overview of current debates and ongoing research in the fields of psychology, political science and sociology. CDSS faculty members will present an outline of their research fields, report on prime examples of their current research, and provide an outlook on potential topics for future research. Doctoral students will have the opportunity to discuss the short talks with the respective lecturer during the remaining discussion time.

    Assignment: Come-up with a research project idea that is informed theoretically or
    methodologically by insights from one or several CDSS faculty presentations (outside of
    your particular field) in this class. Write-up your idea and describe a potential research
    design in a short 3-page paper. The paper is due October 31st.

    Talk schedule

    Schedule
    Lecture
    21.09.20 - 12.10.20 Monday 10:15 - 13:30 Sowi Zoom 18
    BAS: Mathematics for Social Scientists
    2 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: BAS
    Credits: 2
    Course Content

    It is increasingly important for modern social scientists to have a level of mathematical literacy, as mathematical research methods such as statistics and formal modelling have entered the main stream. This course is intended to provide an introduction to mathematical logic and rigour, and to some fundamental mathematical concepts that form the foundation of the modern subject. The course covers introductory set and function theory, including analysis of functions, and includes sections on both probability and linear algebra, which together are the basis of data analysis.

    The exam is scheduled for 15 December from 10.15am

    Basic readings:

    • Knut Sydsaeter and Peter Hammond. 2008. Essential Mathematics for Economic Analysis. 3rd edition. Harlow: Prentice Hall


    Additional readings:

    • Alpha C. Chiang and Kevin Wainwright. 2005. Fundamental Methods of Mathematical Economics. 4th edition. Boston, Mass.: McGraw-Hill
    • Jeff Gill. 2006. Essential Mathematics for Political and Social Research. Cambridge: Cambridge University Press.
    • Malcolm Pemberton and Nicholas Rau. 2007. Mathematics for Economists. 2nd edition. Manchester: Manchester University Press.
    • Carl P. Simon and Lawrence E. Blume. 1994. Mathematics for Economists. New York: W. W. Norton & Company. McGraw-Hill.
    Schedule
    Lecture
    19.10.20 - 30.11.20 Monday 10:15 - 13:30 Sowi Zoom 18
    MET: Crafting Social Science Research
    6 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: MET
    Credits: 6
    Course Content

    All researchers face similar challenges with core issues of research design. A research design is a plan that specifies how you are going to carry out a research project and, particularly, how to use evidence to answer your research question. The goal of this course is to jump-start students with their dissertation proposal. This course should help students to see the trade-offs involved in choosing a particular research design in their research projects. Consequently students are expected to develop own ideas about potential research questions and actively participate in those seminar-style meetings that are organized within this lecture course.

    Course requirements & assessment

    Active participation, draft of dissertation proposal (graded)

    Schedule
    Workshop
    29.09.20 - 08.12.20 Tuesday 12:00 - 13:30 Sowi Zoom 18
    MET: Multivariate Analyses (Theory + Lab Course)
    6 + 2 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: MET
    Credits: 6 + 2
    Course Content

    The course introduces students to quantitative methods in political science. During the first half of the course, we will focus on linear regression models. The topics covered include discussions of the mathematical bases for such models, their estimation and interpretation, model assumptions and techniques for addressing violations of those assumptions, and topics related to model specification and functional forms. During the second half of the course, students will be introduced to likelihood as a theory of inference, including models for binary and count data.

    The main goals of this course are to develop sound critical judgment about quantitative studies of political problems, to understand the logic of statistical inference, to recognize and understand the basics of the linear regression model, to develop the skills necessary to work with datasets to perform basic quantitative analyses, and to provide a basis of knowledge for more advanced statistical methods.

    In the accompanying course "Tutorial Multivariate Analyses" students will develop the necessary expertise in using statistical software to conduct quantitative research in political science.

    Graded assignments include homeworks, a mid-term exam and data analysis projects.

    Schedule
    Lecture
    30.09.20 - 09.12.20 Wednesday 08:30 - 10:00 Sowi Zoom 11
    Tutorial
    30.09.20 - 09.12.20 Wednesday 15:30 - 17:00 Sowi Zoom 4
    01.10.20 - 10.12.20 Thursday 10:15 - 11:45 Sowi Zoom 18
    MET: Theory Building and Causal Inference
    6 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: MET
    Credits: 6
    Course Content

    Questions of cause and effect are at the heart of social science. And yet, establishing credible causal effects in empirical analyses is a difficult enterprise. This course will introduce some of the key conceptual and methodological approaches to tackle the causal inference problem: the potential outcomes model of causal inference, experimental designs, matching and regression, instrumental variables, regression discontinuity designs as well as difference-in-differences and fixed effects.

    Course requirements & assessment

    Active participation, term paper (graded)

    Schedule
    Workshop
    11.09.20 - 23.10.20 Friday 10:15 - 13:30 Sowi Zoom 14
    MET/POL: Game Theory (Theory + Tutorial)
    6 + 2 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: MET/POL
    Credits: 6 + 2
    Course Content

    The objective of this course is to provide students with the basics of formal modeling in political science. The course has some breadth in coverage in the sense that it provides a graduate-level introduction and overview to di erent areas in game theory. It is also narrow in the sense that the emphasis is not on application and model testing but getting trained in reading and writing down formal models. At the conceptual level the course will cover the following topics: normal form games, Nash equilibria, extensive form games, subgame perfect equilibria, repeated games, bargaining, games with incomplete and imperfect information, Bayesian perfect equilibria, signaling games, preferences and individual choices, basics of decision theory and social choice. At the substantial level, we will use these concepts to study, as examples, candidate competition, political lobbying, and war and deterrence.

    Literature
    tba

    Assessment: To pass the course you need an average grade of 4.0 or better in the midterm and the final exam. Final grading of the course will then be based on three components: assignments (20%), mid-term exam (30%), final exam (50%).

    Additional course dates on Tuesday from 3.30 to 5pm (Room: Sowi Zoom 10):

    29 September

    6 October

    13 October

    24 November

    7 December

     

    Tutorial

    This tutorial accompanies the graduate-level introductory lecture in game theory. Its main objective is to practice solution concepts for static and dynamic games of complete and incomplete information.
    The contents are centered on the material covered in the lecture. Thus, the following key areas will be discussed: preferences and individual choices, decision theory, normal form games, Nash equilibria, extensive form games, subgame perfect equilibria, repeated games, bargaining, games with incomplete and imperfect information, Bayesian perfect equilibria, signaling games. At the substantial level, we will use these concepts to study, for instance, candidate competition, political lobbying, and war and deterrence. Students are required to submit four problem sets. Moreover, it is essential for students to prepare thoroughly for all sessions using online tutorials. Active participation in class discussions is expected.

    Course requirements: Four problem sets.

    Schedule
    Lecture
    Additonal slots on Tuesday from 3.30 to 5pm, dates listed under course content 28.09.20 - 07.12.20 Monday 13:45 - 15:15 Sowi Zoom Room 8
    Tutorial
    02.10.20 - 11.12.20 Friday 08:30 - 10:00 Sowi Zoom 08
    RES: CDSS Workshop: Political Science
    2 or 3 depending on applicable study regulations ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: RES
    Credits: 2 or 3 depending on applicable study regulations
    Course Content

    Participation is mandatory for first to third year CDSS students of Political Science. Participation is recommended for later CDSS PhD candidates, but to no credit.

    Other young researchers in the social sciences affiliated with the University of Mannheim (incl. MZES and SFB 884) are also invited to attend the talks.

    The goal of this course is to provide support and crucial feedback for CDSS doctoral students on their ongoing dissertation project. In this workshop they are expected to play two roles - provide feedback to their peers as well as present their own work in order to receive feedback.

    In order to receive useful feedback, participants are asked to circulate their paper and two related published pieces of research one week before the talk.

    Schedule
    Workshop
    30.09.20 - 09.12.20 Wednesday 12:00 - 13:30 Sowi Zoom 04
    RES: MZES B Colloquium "European Political Systems and their Integration"
    2 ECTS
    Course Type: core course
    Course Number: RES
    Credits: 2
    Course Content

    Please refer to the MZES webpages for dates and times.

    RES: SFB 884 Seminar Series
    2 ECTS
    Course Type: core course
    Course Number: RES
    Credits: 2
    Prerequisites

    CSSR, TBCI, Dissertation Proposal

    Course Content

    Attending the Seminar Series on the Political Economy of Reforms is a possible alternative to attending the MZES B colloquium. Please refer to the SFB 884 website for dates and times.

    MET: Cross Sectional Data Analysis (Lecture + Tutorial)
    6 + 3 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 6 + 3
    Prerequisites

    Sound understanding of linear regression models (OLS), knowledge in linear algebra and calculus, and being familiar with the statistical package Stata.

    Course Content

    The main focus lies on the introduction to statistical models and estimators beyond linear regression useful to a social scientists. A good understanding of the classical linear regression model is a prerequisite and required for the further topics of the course. We will first discuss violations of the asymptotic properties of the linear regression model and ways to address these violations (heteroscedasticity, endogeneity, proxy variables, IV-estimator). The second part of the class is dedicated to rst the maximum likelihood estimator and second to generalized linear models (GLS) for binary choice decisions (Logit, Probit), ordinal dependent variables, and count data (Poisson, Negative Binomial). Classes will be accompanied by lab sessions to repeat and practice the topics from the classes. We will use the statistical package Stata.

    Course requirements & assessment

    •  Regular and active participation in the lab sessions.
    •  Presentation of a weekly exercise; you must hand in the slides of the presentation, the Stata syntax file and output of the respective exercise, and a short output interpretation.
    • written exam (graded, 90 min)

    Credits (9 ECTS for lecture & tutorial) will be awarded based on a passed written exam. Participation in the final exam is subject to having passed all course requirements as stated above.

     

    Schedule
    Lecture
    29.09.20 - 08.12.20 Tuesday 13:45 - 15:15 B 144 in A5, 6 or online Zoom B144
    Tutorial
    30.09.20 - 09.12.20 Wednesday 13:45 - 15:15 Sowi Zoom 08
    MET: Data and Measurement (Lecture + Tutorial)
    6 + 2 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 6 + 2
    Course Content

    Summary

    This course gives an overview of data used in political science and their measurement properties. At the beginning of the course we will focus on survey data and traditional statistics and move to data science approaches for big data towards the end of the course. Topics covered include the Total Survey Error (TSE) framework, operationalizing research questions, guidelines for writing survey questions, testing questions with cognitive interviews and eye-tracking, sampling, coverage, and nonresponse of survey and big data, and data analytics approaches in data science.

    Course assessment & requirements

    3 mock exams (pass/fail, Hausarbeit), active participation, term paper (graded)

    Schedule
    Lecture
    29.09.20 - 08.12.20 Tuesday 08:30 - 10:00 Sowi Zoom 01
    Tutorial
    29.09.20 - 08.12.20 Tuesday 10:15 - 11:45 Sowi Zoom 01
    MET: Programming in R and beyond
    4 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 4
    Course Content

    The software R is a computer programming language designed for statistical analysis and graphics. The first part of the course deals with a basic introduction to R, i.e. data handling, basic statistical analyses, the creation of graphics, and linear modeling including test for specially designed hypotheses. In the second part we use R as a programming language for cognitive modeling. We will simulate data based on mathematical models of cognitive functions and analyze these data with maximum likelihood parameter estimation techniques. At the end, I will introduce some advanced techniques, for example the creation of statistical reports with R.
    The software package R is free and available on all major platforms (www.r-project.org). I also recommend the free and platform independent Software RStudio as a comfortable IDE for R (www.rstudio.com). A basic introduction to R can be found under:

    http://cran.r-project.org/doc/manuals/r-release/R-intro.pdf.

    Literature will be given during the course

    Academic assessment  - regular participation in the course; non-graded test

    Schedule
    Seminar
    biweekly 02.10.20 - 11.12.20 Friday 13:45 - 17:00 Sowi Zoom 02
    MET: Research Design (Lecture + Tutorial)
    6 + 3 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 6 + 3
    Course Content

    How do we know which research design fits best our research question? What requirements must be in place for good descriptive, causal and predictive inference? How do we estimate causal effects? How do we design and analyze experiments? Can we make causal claims from observational data? Researchers in the social sciences must be able to answer all of these questions.
    This course teaches the fundamental concepts behind the estimation of causal effects, including potential obstacles to causal inference. Real-world examples will be discussed in detail and students will apply the techniques learned with real datasets in R. Students will come away with an understanding of how to estimate causal effects in both randomized and observational settings, with a particular focus on the careful design of both types of studies.

    Tutorial

    In the practice sessions, students will learn how to implement causal inference methods in R. Students should bring their own laptop for the all practice sessions. Previous knowledge in R is not necessary although advantageous. Please make also sure to install R and R studio before the first practice session.

    Course requirements & assessment

    Homework, oral participation, presentation ,written exam (graded)

    Schedule
    Lecture
    01.10.20 - 10.12.20 Thursday 13:45 - 15:15 Sowi Zoom 10
    Tutorial
    01.10.20 - 10.12.20 Thursday 15:30 - 17:00 Sowi Zoom 14
    MET: SMiP - Research Training Group 'Statistical Modeling in Psychology' additional courses (CDSS only)
    Various ECTS
    Course Type: elective course
    Course Number: MET
    Credits: Various
    Course Content

    Further SMiP courses open to CDSS doctoral students are:

    Hands-on browser-based Experimentation Instructor: Felix Henninger, Date: 05. - 09.10.2020 (16:30 - 18:30) and 1 afternoon mid October, Location: remote (invitation via email for registered participants). PLUS: The instructor will share slides with audio explanations to study before the interactive online sessions.

    Introduction to R: Basics Instructor: Martin Schnuerch, Date: 29.10.2020 (10:00 - 18:00), Location: Mannheim or Heidelberg **

    Introduction to R: Advanced Instructor: Martin Schnuerch, Date: 30.10.2020 (09:00 - 17:00), Location: Mannheim or Heidelberg **

    Cognitive Modeling in R Instructor: Klaus Oberauer, Dates: 05.11. & 06.11.2020, Location: Mannheim or remote

    Even more power for SMiP: Basic and advanced statistical power analysis using G*Power and multiTree Instructor: Edgar Erdfelder, Date: 27.11.2020 (13:00 - 17:00), Location: remote (invitation via email for registered participants). PLUS: The instructor will share slides with audio explanations to study before the interactive online session.

    Evidence, Errors, and Belief: A Stroll through the Statistical Inference Maze Instructor: Martin Schnuerch, Dates: 10.12. and 11.12.2020 (14:00 - 18:00), Location: remote, invitation via email for registered participants. PLUS: The instructor will share prep materials to study before the interactive online sessions.

    Improving your statistical questions Instructor: Daniel Lakens, Dates: 21.01. & 22.01.2021, Location: Freiburg or remote

    Registration for SMiP courses must be done directly via Annette Förster, SMiP Administration Assistant.

    Further details and registration.

    MET: SMiP Foundations of Statistical Modeling (CDSS only)
    6 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 6
    Course Content

    This course gives an advanced overview of standard multivariate methods and current developments in multivariate modeling. The topics include general and generalized linear models, structural equation models, multilevel modeling and specific models for the analysis of time-related effects. In the morning sessions, we will provide the formal foundations and theoretical background of the model classes for continuous and discrete observations. The afternoon sessions focus on empirical applications and hands-on exercises in data analysis.
    The goals are to bring the PhD candidates to a common level of statistical knowledge and data analytic skills and to set the stage for the more specialized topics in the Foundations 2 course and workshops in the following semesters.

    Dates

    Foundations 1 (Instructor: Thorsten Meiser, Assignment: Exercises in statistical modeling and analysis)

    15.10. (09:30 - 17:30) and 16.10.2020 (09:00 - 17:00), Location: Mannheim or Heidelberg

    19.11. (14:00 - 17:00) and 20.11.2020 (14:00 - 17:00), Location: remote, invitation via email for registered participants. PLUS: The instructor will share prep materials to study before the interactive online sessions.

    2 days mid December / beginning of January, Location: Mannheim

    Further details can be found on the web page of the RTG 'Statistical Modeling in Psychology'

    MET/PSY: Theories and Methods in Social Psychology
    4 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET/PSY
    Credits: 4
    Course Content

    This seminar has a particular focus on research activities in social psychology. Unlike seminars that concentrate on one core thematic topic, this seminar will address a selected variety of different research topics in current social psychology. In each seminar session we will have a presentation either by participating Ph.D. students or by members of the social psychology group. Each presentation will address a current research topic in social psychology. The seminar provides the opportunity to actively discuss methodological, theoretical, and applied implications of the presented research. A particular focus will rest on the discussion of general methodological aspects.

    Literature: Will be announced in the seminar

    Examination (graded): Awarded for (a) active participation in the seminar discussions, (b) own presentation, and (c) homework. Grades are based on the homework (essay).

    Schedule
    Seminar
    01.10.20 - 10.12.20 Thursday 13:45 - 15:15 Sowi Zoom 03
    POL: Advanced Topics in Comparative Politics: Free Speech and Censorship
    10 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: POL
    Credits: 10
    Course Content

    To openly express one’s views is the most fundamental civil liberty. While this basic right is under constant and serious threat in authoritarian contexts, the question of how free speech should be regulated is also a concern in liberal democracies. It is particularly important in globalized conditions of cultural diversity and the unprecedented levels of communication facilitated by the digital revolution. The aim of this course is to discuss contemporary scholarly research on the politics of free speech and censorship. Why is free expression so important? Why and how do states actually regulate free speech and what are the effects of this regulation? How does cultural diversity and digital communication impact on these questions? Next to substantive discussion the course will place great emphasis on the practice of quantitative political research and provide ample space for students’ projects.

    Course requirements & assessment

    Participation, term paper (graded)

    Schedule
    Seminar
    01.10.20 - 10.12.20 Thursday 15:30 - 17:00 Sowi Zoom 01
    POL: Advanced Topics in Comparative Politics: Political Behavior in Context
    10 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: POL
    Credits: 10
    Course Content

    Political behavior takes place in context. This statement is a truism and implies several challenges at the same time. Context is a multidimensional concept comprising – inter alia – social, political, and institutional features. At the theoretical level, the diversity of dimensions requires careful consideration of how to integrate contextual features into individual-level models of political behavior. Moreover, combining data from different levels of aggregation to examine the role of contexts in individual-level behavior raises several methodological issues. In this seminar, we will address the conceptual, theoretical, and methodological issues in the analysis of contextual effects on individual-level political behavior. Students will review the latest empirical studies in the field and prepare research papers in which they analyze specific questions using available data sets.

    Office hours: Tuesday, 14.30-15.30 in Room A 343, A 5

    Course requirements & assessment

    Oral presentation of a literature review and active participation during the sessions
    Term Paper (ca. 8.000 words, graded)

    Schedule
    Seminar
    29.09.20 - 08.12.20 Tuesday 12:00 - 13:30 Sowi Zoom 03
    POL: Advanced Topics in International Politics: Agents of Political Violence
    10 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: POL
    Credits: 10
    Course Content

    This seminar discusses seminal and current work on agents of political violence. We analyze the role and characteristics of the military, including drivers and counterstrategies to coup d’états. A large part of the course will focus on irregular armed agents that are aligned with the stage, engaging with the growing research on militias, death squads, civil defense forces and paramilitary groups. We assess national and transnational drivers of their formation, their termination, how they affect political violence during and outside of civil wars. The seminar will be student-led. Over the course of the seminar you will develop your own research question on one of the topics discussed in the seminar and carry out your own research. Additionally, you are expected to write one book review, read all required materials, engage in the discussions and provide feedback on other student’s work.

    Course requirements & assessment

    • Participation in and contributions to class discussions of readings and the key topics
    • One book review (1,000 words, potentially for submission to International Studies Review)
    • Feedback on a student’s research proposal
    • Leading one seminar session.
    • Research paper (graded)

    Literature

    Required readings are indicated in the course schedule, which are based on seminal and current research on agents of political violence. Each session requires a significant amount of reading. Focus on the key arguments. You are not expected to know the details of all readings, or specific empirical strategies, results or facts. The specific topics and readings may change based on the interests of the class.

    Schedule
    Seminar
    29.09.20 - 08.12.20 Tuesday 13:45 - 15:15 Sowi Zoom 01
    POL: Advanced Topics in International Politics: Replicating European Studies
    10 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: POL
    Credits: 10
    Course Content

    In this seminar we will replicate empirical analysis regarding topics of European (dis)integration. Students are free to select the analysis to be replicated, for which they need to find the data and the file of the statistical analysis. A central focus will be on the research design, in particular the conceptual decisions of data generation and analysis. After replication, several robustness checks are to be carried out and alternative research designs will be discussed and eventually applied. A summary paper (12-15) of the experiences and results is required and needs to be submitted at the end of the semester.

    Course requirements & assessment

    Active attendance, term paper (graded)

    Schedule
    Seminar
    01.10.20 - 10.12.20 Thursday 12:00 - 13:30 Sowi Zoom 01
  • Psychology

    BAS: Current Research Perspectives
    2 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: BAS
    Credits: 2
    Course Content

    The course "Current Research Perspectives" introduces first year doctoral students to the theoretically informed research approaches and substantive research fields that build the strongholds of social science research in Mannheim. A series of talks provides first year doctoral students with an overview of current debates and ongoing research in the fields of psychology, political science and sociology. CDSS faculty members will present an outline of their research fields, report on prime examples of their current research, and provide an outlook on potential topics for future research. Doctoral students will have the opportunity to discuss the short talks with the respective lecturer during the remaining discussion time.

    Assignment: Come-up with a research project idea that is informed theoretically or
    methodologically by insights from one or several CDSS faculty presentations (outside of
    your particular field) in this class. Write-up your idea and describe a potential research
    design in a short 3-page paper. The paper is due October 31st.

    Talk schedule

    Schedule
    Lecture
    21.09.20 - 12.10.20 Monday 10:15 - 13:30 Sowi Zoom 18
    BAS: Mathematics for Social Scientists
    2 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: BAS
    Credits: 2
    Course Content

    It is increasingly important for modern social scientists to have a level of mathematical literacy, as mathematical research methods such as statistics and formal modelling have entered the main stream. This course is intended to provide an introduction to mathematical logic and rigour, and to some fundamental mathematical concepts that form the foundation of the modern subject. The course covers introductory set and function theory, including analysis of functions, and includes sections on both probability and linear algebra, which together are the basis of data analysis.

    The exam is scheduled for 15 December from 10.15am

    Basic readings:

    • Knut Sydsaeter and Peter Hammond. 2008. Essential Mathematics for Economic Analysis. 3rd edition. Harlow: Prentice Hall


    Additional readings:

    • Alpha C. Chiang and Kevin Wainwright. 2005. Fundamental Methods of Mathematical Economics. 4th edition. Boston, Mass.: McGraw-Hill
    • Jeff Gill. 2006. Essential Mathematics for Political and Social Research. Cambridge: Cambridge University Press.
    • Malcolm Pemberton and Nicholas Rau. 2007. Mathematics for Economists. 2nd edition. Manchester: Manchester University Press.
    • Carl P. Simon and Lawrence E. Blume. 1994. Mathematics for Economists. New York: W. W. Norton & Company. McGraw-Hill.
    Schedule
    Lecture
    19.10.20 - 30.11.20 Monday 10:15 - 13:30 Sowi Zoom 18
    MET: Crafting Social Science Research
    6 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: MET
    Credits: 6
    Course Content

    All researchers face similar challenges with core issues of research design. A research design is a plan that specifies how you are going to carry out a research project and, particularly, how to use evidence to answer your research question. The goal of this course is to jump-start students with their dissertation proposal. This course should help students to see the trade-offs involved in choosing a particular research design in their research projects. Consequently students are expected to develop own ideas about potential research questions and actively participate in those seminar-style meetings that are organized within this lecture course.

    Course requirements & assessment

    Active participation, draft of dissertation proposal (graded)

    Schedule
    Workshop
    29.09.20 - 08.12.20 Tuesday 12:00 - 13:30 Sowi Zoom 18
    MET: Theory Building and Causal Inference
    6 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: MET
    Credits: 6
    Course Content

    Questions of cause and effect are at the heart of social science. And yet, establishing credible causal effects in empirical analyses is a difficult enterprise. This course will introduce some of the key conceptual and methodological approaches to tackle the causal inference problem: the potential outcomes model of causal inference, experimental designs, matching and regression, instrumental variables, regression discontinuity designs as well as difference-in-differences and fixed effects.

    Course requirements & assessment

    Active participation, term paper (graded)

    Schedule
    Workshop
    11.09.20 - 23.10.20 Friday 10:15 - 13:30 Sowi Zoom 14
    RES: AC2/BC3 Colloquia I
    2 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: RES
    Credits: 2
    Prerequisites

    Please check with individual chairs in the Psychology Department for dates and times of research colloquia as well as registration.

    RES: CDSS Workshop: Research in Psychology
    2 or 3 depending on applicable study regulations ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: RES
    Credits: 2 or 3 depending on applicable study regulations
    Course Content

    Participation is mandatory for first to third year CDSS doctoral students of Psychology. Participation is recommended for later CDSS doctoral students, but to no credit.

    Research in Cognitive Psychology: Research projects in cognitive psychology and neuropsychology are planned, conducted, analyzed, and discussed.

     Application via 'Studierendenportal' is necessary to have access to the course material provided in ILIAS.

    Open office hours:
    Prof. Dr. Erdfelder: Thursday, 10.15h - 11.45h.


    Literature: References will be given during the course.

    Competences acquired

    Improvement in research skills and communication of research results.

    Schedule
    Workshop
    28.09.20 - 07.12.20 Monday 15:30 - 17:00 Sowi Zoom 06
    RES: English Academic Writing for Psychologists 1st part (CDSS only)
    1 ECTS
    Lecturer(s)
    Course Type: core course
    Course Number: RES
    Credits: 1
    Course Content

    Training Writing Research Proposals Instructor: Benjamin Hilbig, Date: 14.11.2020 (09:30 - 17:30) the in person training has been cancelled. The instructor will share a short video tutorial with the registered participants. Some course contents will be postponed to next semester's training.

    MET: Cross Sectional Data Analysis (Lecture + Tutorial)
    6 + 3 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 6 + 3
    Prerequisites

    Sound understanding of linear regression models (OLS), knowledge in linear algebra and calculus, and being familiar with the statistical package Stata.

    Course Content

    The main focus lies on the introduction to statistical models and estimators beyond linear regression useful to a social scientists. A good understanding of the classical linear regression model is a prerequisite and required for the further topics of the course. We will first discuss violations of the asymptotic properties of the linear regression model and ways to address these violations (heteroscedasticity, endogeneity, proxy variables, IV-estimator). The second part of the class is dedicated to rst the maximum likelihood estimator and second to generalized linear models (GLS) for binary choice decisions (Logit, Probit), ordinal dependent variables, and count data (Poisson, Negative Binomial). Classes will be accompanied by lab sessions to repeat and practice the topics from the classes. We will use the statistical package Stata.

    Course requirements & assessment

    •  Regular and active participation in the lab sessions.
    •  Presentation of a weekly exercise; you must hand in the slides of the presentation, the Stata syntax file and output of the respective exercise, and a short output interpretation.
    • written exam (graded, 90 min)

    Credits (9 ECTS for lecture & tutorial) will be awarded based on a passed written exam. Participation in the final exam is subject to having passed all course requirements as stated above.

     

    Schedule
    Lecture
    29.09.20 - 08.12.20 Tuesday 13:45 - 15:15 B 144 in A5, 6 or online Zoom B144
    Tutorial
    30.09.20 - 09.12.20 Wednesday 13:45 - 15:15 Sowi Zoom 08
    MET: Data and Measurement (Lecture + Tutorial)
    6 + 2 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 6 + 2
    Course Content

    Summary

    This course gives an overview of data used in political science and their measurement properties. At the beginning of the course we will focus on survey data and traditional statistics and move to data science approaches for big data towards the end of the course. Topics covered include the Total Survey Error (TSE) framework, operationalizing research questions, guidelines for writing survey questions, testing questions with cognitive interviews and eye-tracking, sampling, coverage, and nonresponse of survey and big data, and data analytics approaches in data science.

    Course assessment & requirements

    3 mock exams (pass/fail, Hausarbeit), active participation, term paper (graded)

    Schedule
    Lecture
    29.09.20 - 08.12.20 Tuesday 08:30 - 10:00 Sowi Zoom 01
    Tutorial
    29.09.20 - 08.12.20 Tuesday 10:15 - 11:45 Sowi Zoom 01
    MET: Multivariate Analyses (Theory + Lab Course)
    6 + 2 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 6 + 2
    Course Content

    The course introduces students to quantitative methods in political science. During the first half of the course, we will focus on linear regression models. The topics covered include discussions of the mathematical bases for such models, their estimation and interpretation, model assumptions and techniques for addressing violations of those assumptions, and topics related to model specification and functional forms. During the second half of the course, students will be introduced to likelihood as a theory of inference, including models for binary and count data.

    The main goals of this course are to develop sound critical judgment about quantitative studies of political problems, to understand the logic of statistical inference, to recognize and understand the basics of the linear regression model, to develop the skills necessary to work with datasets to perform basic quantitative analyses, and to provide a basis of knowledge for more advanced statistical methods.

    In the accompanying course "Tutorial Multivariate Analyses" students will develop the necessary expertise in using statistical software to conduct quantitative research in political science.

    Graded assignments include homeworks, a mid-term exam and data analysis projects.

    Schedule
    Lecture
    30.09.20 - 09.12.20 Wednesday 08:30 - 10:00 Sowi Zoom 11
    Tutorial
    30.09.20 - 09.12.20 Wednesday 15:30 - 17:00 Sowi Zoom 4
    01.10.20 - 10.12.20 Thursday 10:15 - 11:45 Sowi Zoom 18
    MET: Programming in R and beyond
    4 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 4
    Course Content

    The software R is a computer programming language designed for statistical analysis and graphics. The first part of the course deals with a basic introduction to R, i.e. data handling, basic statistical analyses, the creation of graphics, and linear modeling including test for specially designed hypotheses. In the second part we use R as a programming language for cognitive modeling. We will simulate data based on mathematical models of cognitive functions and analyze these data with maximum likelihood parameter estimation techniques. At the end, I will introduce some advanced techniques, for example the creation of statistical reports with R.
    The software package R is free and available on all major platforms (www.r-project.org). I also recommend the free and platform independent Software RStudio as a comfortable IDE for R (www.rstudio.com). A basic introduction to R can be found under:

    http://cran.r-project.org/doc/manuals/r-release/R-intro.pdf.

    Literature will be given during the course

    Academic assessment  - regular participation in the course; non-graded test

    Schedule
    Seminar
    biweekly 02.10.20 - 11.12.20 Friday 13:45 - 17:00 Sowi Zoom 02
    MET: Research Design (Lecture + Tutorial)
    6 + 3 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 6 + 3
    Course Content

    How do we know which research design fits best our research question? What requirements must be in place for good descriptive, causal and predictive inference? How do we estimate causal effects? How do we design and analyze experiments? Can we make causal claims from observational data? Researchers in the social sciences must be able to answer all of these questions.
    This course teaches the fundamental concepts behind the estimation of causal effects, including potential obstacles to causal inference. Real-world examples will be discussed in detail and students will apply the techniques learned with real datasets in R. Students will come away with an understanding of how to estimate causal effects in both randomized and observational settings, with a particular focus on the careful design of both types of studies.

    Tutorial

    In the practice sessions, students will learn how to implement causal inference methods in R. Students should bring their own laptop for the all practice sessions. Previous knowledge in R is not necessary although advantageous. Please make also sure to install R and R studio before the first practice session.

    Course requirements & assessment

    Homework, oral participation, presentation ,written exam (graded)

    Schedule
    Lecture
    01.10.20 - 10.12.20 Thursday 13:45 - 15:15 Sowi Zoom 10
    Tutorial
    01.10.20 - 10.12.20 Thursday 15:30 - 17:00 Sowi Zoom 14
    MET: SMiP - Research Training Group 'Statistical Modeling in Psychology' additional courses (CDSS only)
    Various ECTS
    Course Type: elective course
    Course Number: MET
    Credits: Various
    Course Content

    Further SMiP courses open to CDSS doctoral students are:

    Hands-on browser-based Experimentation Instructor: Felix Henninger, Date: 05. - 09.10.2020 (16:30 - 18:30) and 1 afternoon mid October, Location: remote (invitation via email for registered participants). PLUS: The instructor will share slides with audio explanations to study before the interactive online sessions.

    Introduction to R: Basics Instructor: Martin Schnuerch, Date: 29.10.2020 (10:00 - 18:00), Location: Mannheim or Heidelberg **

    Introduction to R: Advanced Instructor: Martin Schnuerch, Date: 30.10.2020 (09:00 - 17:00), Location: Mannheim or Heidelberg **

    Cognitive Modeling in R Instructor: Klaus Oberauer, Dates: 05.11. & 06.11.2020, Location: Mannheim or remote

    Even more power for SMiP: Basic and advanced statistical power analysis using G*Power and multiTree Instructor: Edgar Erdfelder, Date: 27.11.2020 (13:00 - 17:00), Location: remote (invitation via email for registered participants). PLUS: The instructor will share slides with audio explanations to study before the interactive online session.

    Evidence, Errors, and Belief: A Stroll through the Statistical Inference Maze Instructor: Martin Schnuerch, Dates: 10.12. and 11.12.2020 (14:00 - 18:00), Location: remote, invitation via email for registered participants. PLUS: The instructor will share prep materials to study before the interactive online sessions.

    Improving your statistical questions Instructor: Daniel Lakens, Dates: 21.01. & 22.01.2021, Location: Freiburg or remote

    Registration for SMiP courses must be done directly via Annette Förster, SMiP Administration Assistant.

    Further details and registration.

    MET: SMiP Foundations of Statistical Modeling (CDSS only)
    6 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET
    Credits: 6
    Course Content

    This course gives an advanced overview of standard multivariate methods and current developments in multivariate modeling. The topics include general and generalized linear models, structural equation models, multilevel modeling and specific models for the analysis of time-related effects. In the morning sessions, we will provide the formal foundations and theoretical background of the model classes for continuous and discrete observations. The afternoon sessions focus on empirical applications and hands-on exercises in data analysis.
    The goals are to bring the PhD candidates to a common level of statistical knowledge and data analytic skills and to set the stage for the more specialized topics in the Foundations 2 course and workshops in the following semesters.

    Dates

    Foundations 1 (Instructor: Thorsten Meiser, Assignment: Exercises in statistical modeling and analysis)

    15.10. (09:30 - 17:30) and 16.10.2020 (09:00 - 17:00), Location: Mannheim or Heidelberg

    19.11. (14:00 - 17:00) and 20.11.2020 (14:00 - 17:00), Location: remote, invitation via email for registered participants. PLUS: The instructor will share prep materials to study before the interactive online sessions.

    2 days mid December / beginning of January, Location: Mannheim

    Further details can be found on the web page of the RTG 'Statistical Modeling in Psychology'

    MET/POL: Game Theory (Theory + Tutorial)
    6 + 2 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET/POL
    Credits: 6 + 2
    Course Content

    The objective of this course is to provide students with the basics of formal modeling in political science. The course has some breadth in coverage in the sense that it provides a graduate-level introduction and overview to di erent areas in game theory. It is also narrow in the sense that the emphasis is not on application and model testing but getting trained in reading and writing down formal models. At the conceptual level the course will cover the following topics: normal form games, Nash equilibria, extensive form games, subgame perfect equilibria, repeated games, bargaining, games with incomplete and imperfect information, Bayesian perfect equilibria, signaling games, preferences and individual choices, basics of decision theory and social choice. At the substantial level, we will use these concepts to study, as examples, candidate competition, political lobbying, and war and deterrence.

    Literature
    tba

    Assessment: To pass the course you need an average grade of 4.0 or better in the midterm and the final exam. Final grading of the course will then be based on three components: assignments (20%), mid-term exam (30%), final exam (50%).

    Additional course dates on Tuesday from 3.30 to 5pm (Room: Sowi Zoom 10):

    29 September

    6 October

    13 October

    24 November

    7 December

    Tutorial

    This tutorial accompanies the graduate-level introductory lecture in game theory. Its main objective is to practice solution concepts for static and dynamic games of complete and incomplete information.
    The contents are centered on the material covered in the lecture. Thus, the following key areas will be discussed: preferences and individual choices, decision theory, normal form games, Nash equilibria, extensive form games, subgame perfect equilibria, repeated games, bargaining, games with incomplete and imperfect information, Bayesian perfect equilibria, signaling games. At the substantial level, we will use these concepts to study, for instance, candidate competition, political lobbying, and war and deterrence. Students are required to submit four problem sets. Moreover, it is essential for students to prepare thoroughly for all sessions using online tutorials. Active participation in class discussions is expected.

    Course requirements: Four problem sets.

    Schedule
    Lecture
    Additonal slots on Tuesday from 3.30 to 5pm, dates listed under course content 28.09.20 - 07.12.20 Monday 13:45 - 15:15 Sowi Zoom Room 8
    Tutorial
    02.10.20 - 11.12.20 Friday 08:30 - 10:00 Sowi Zoom 08
    MET/PSY: Theories and Methods in Social Psychology
    4 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: MET/PSY
    Credits: 4
    Course Content

    This seminar has a particular focus on research activities in social psychology. Unlike seminars that concentrate on one core thematic topic, this seminar will address a selected variety of different research topics in current social psychology. In each seminar session we will have a presentation either by participating Ph.D. students or by members of the social psychology group. Each presentation will address a current research topic in social psychology. The seminar provides the opportunity to actively discuss methodological, theoretical, and applied implications of the presented research. A particular focus will rest on the discussion of general methodological aspects.

    Literature: Will be announced in the seminar

    Examination (graded): Awarded for (a) active participation in the seminar discussions, (b) own presentation, and (c) homework. Grades are based on the homework (essay).

    Schedule
    Seminar
    01.10.20 - 10.12.20 Thursday 13:45 - 15:15 Sowi Zoom 03
    PSY: Advanced topics in Cognitive Psychology
    4 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: PSY
    Credits: 4
    Course Content

    This Lecture provides an advanced treatment of research methods in cognitive psychology as well as an overview of research topics of Cognitive Psychology in Mannheim.

    Exemplary Topics

    •     Basic methodology of Cognitive Psychology
    •     Stochastic Modeling of Cognitive Processes
    •     Model selection
    •     Information Search in Decision Making
    •     Visual short-term memory
    •     Investigating cognitive processes using mouse-tracking
    •     Strategy Contributions to Cognitive Aging
    •     The Truth Effect

    Literature

    • Farrell, S. & Lewandowsky, S. (2018). Computational modeling of cognition and behavior. Cambridge, UK: Cambridge University Press. (Chapters 1-5, 10, 12)
    • Quinlan, P. & Dyson, B. (2008). Cognitive psychology. Harlow, UK: Pearson.(Chapters 1 & 2)


    Assessment: Written exam (90 mins, graded)

    Competences acquired

    Knowledge of the main research strategies and theoretical developments in the study of memory; ability to discuss empirical studes critically

    Schedule
    Lecture
    01.10.20 - 10.12.20 Thursday 15:30 - 17:00 Sowi Zoom 05
    PSY: Research in Clinical Psychology
    3 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: PSY
    Credits: 3
    Course Content

    We invite CDSS doctoral candidates to discuss their research with experts in the field. The chair of Clinical Psychology and Biological Psychology and Psychotherapy pursues a wide range of topics and brings together a large spectrum of research approaches. We address open questions regarding each step of creative research and prolific publication of our scientific results. Each week we select one or two of our own projects for discussion.

    Schedule
    Seminar
    29.09.20 - 08.12.20 Tuesday 08:30 - 10:00 Sowi Zoom 18
    PSY: Work and Organizational Psychology: Emotion Regulation
    4 ECTS
    Lecturer(s)
    Course Type: elective course
    Course Number: PSY
    Credits: 4
    Course Content

    This seminar will deal with the topic of emotion regulation at the workplace.
    In increasing interdependence work environments and a growing service sector, emotion regulation is an important issue for consideration.
    In this seminar, we therefore deal with what is the role of emotion regulation in everyday work, what are the antecedents and consequences of different emotion regulation strategies, and how organizations take part in these processes.

    We will discuss theoretical models, as well as empirical findings, and practical implications.

    Course requirements & assessment

    Active participation, homework assignments, presentation, term paper (graded)

    Schedule
    Seminar
    30.09.20 - 09.12.20 Wednesday 08:30 - 10:00 Sowi Zoom 08