Course Catalog

MET: Crafting Social Science Research

Lecturer(s)

Emre Can Oral

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 tbc

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

Workshop
biweekly	13.09.23 – 06.12.23	Wednesday	13:45 – 17:00	211 in B6, 30–32	Link

RES: CDSS Workshop: Sociology

Lecturer(s)

Thomas Gschwend

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.

The goal of this course is to jump-start students with their dissertation proposal. Such a proposal is a research outline that delineates the doctoral thesis project, including the motivation for research question(s), the survey of the relevant theoretical and empirical contributions, the development of a theoretical framework, the specification of the methodology and planned empirical analysis. You should be prepared to address the following questions: What makes that an interesting question? Is it an important question? What contributions would this question and the answers make to the scholarly literature? What strategies are there to answer your research question(s)?

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

Mandatory readings, active participation in class, homework assignments, presentation of research proposal and performing as a discussant of proposals of peers in a workshop format, research proposal term paper (circa 10 pages, graded)

Schedule

Workshop
	05.09.23 – 05.12.23	Tuesday	10:15 – 11:45	211 in B6, 30–32	Link

Lecturer(s)

Florian Keusch

Course Type: core course

Course Number: RES

Credits: 2

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.

Dates will be determined closer to the time in conjunction with all participants.

RES: Colloquia

MET: Bayesian Statistics in the Social Sciences

Course Type: core course

Course Number: RES

Credits: 2

Course Content

CDSS doctoral students in political science and sociology can choose freely which weekly colloquium to attend. Colloquia must be attended regularly in year two and three of doctoral studies.

Please choose from

MZES A Colloquium “European Societies and their Integration”

MZES Colloquium B “European Political Systems and their Integration”

Please refer to the MZES webpage for all further details. The talk announcements will be communicated via the CDSS mailing list as well.

Alternatively you can attend the Mannheim Research Colloquium on Survey Methods (MaRCS), which will be announced through the Faculty of Social Sciences mailing list.

All 2nd and 3rd year students must hand in a list of colloquia attended in that semester to receive the 2 ECTS. As with any other course, an attandance of at least 80% of the courses is required.

MET: Cross Sectional Data Analysis (Lecture + Tutorial)

Course Type: elective course

Course Number: MET

Credits: 6

Prerequisites

Knowledge of statistics and empirical social research methods

Course Content

Selected topics relating to Bayesian statistics in the social sciences are introduced in this seminar. Assigned readings and in-class activities will impart a deeper insight into the current status of research in this field, which is used to determine open questions and perspectives for further research.

Course taught by Prof. Joe Sakshaug.

Learning outcomes: Upon completion of the module, students are able to:

• present their basic knowledge in Bayesian statistics applied to social science research fields
• name the latest methodological developments in Bayesian social science research
• describe their in-depth knowledge of empirical approaches to Bayesian inference in the social science research fields covered
• critically evaluate the empirical literature and applications of Bayesian statistics in the social science research fields covered

Course requirements & assessment

Students write a term paper (5,000 words max.) where they either
1) carry out an empirical study in a focus area of social science research using Bayesian methods, OR
2) conduct a critical literature review of Bayesian methods used in the social sciences.

The course is evaluated as 'pass/fail'.

Schedule

Seminar
	08.09.23 – 08.12.23	Friday	08:30 – 10:00	Online

MET: Quantitative Methods (formerly Multivariate Analyses (Theory + Lab Course))

Lecturer(s)

Thomas Gautschi

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
	05.09.23 – 05.12.23	Tuesday	13:45 – 15:15	A 103 in B6, 23–25	Link
Tutorial
Danielle Martin	05.09.23 – 05.12.23	Tuesday	15:30 – 17:00	D002 in B6, 27–29
Sandra Morgenstern	07.09.23 – 07.12.23	Thursday	12:00 – 13:30	B318, in A5, 6 entrance B

MET: Research Design (Lecture + Tutorial)

Lecturer(s)

Thomas Gschwend

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.

The lab sessions will focus on the practical issues associated with quantitative methods, including obtaining and preparing data sets, how to use statistical software, which tests to use for different kinds of problems, how to graph data effectively for presentation and analysis, and how to interpret results. The seminar will also serve as a software tutorial. No prior knowledge of statistical programming is expected

Course requirements & assessment

Homework, participation, take-home exam (graded)

Schedule

Lecture
	06.09.23 – 06.12.23	Wednesday	08:30 – 10:00	B 244 in A5,6	Link
	02.11.23	Thursday	08:30 – 10:00	B 244 in A5,6 entrance B
Tutorial
Oliver Rittmann	07.09.23 – 07.12.23	Thursday	10:15 – 11:45	310 in B6, 30–32	Link
Domantas Undzenas	08.09.23 – 08.12.23	Friday	10:15 – 11:45	A102 in B6, 23–25	Link

MET: SMiP – Research Training Group 'Statistical Modeling in Psychology' additional courses (CDSS only)

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

Lecture: Participation, written exam (graded)
Tutorial: Homework, oral participation, presentation

The course will be taught by Nan Zhang, PhD

Schedule

Lecture
	07.09.23 – 07.12.23	Thursday	10:15 – 11:45	B143, in A5, 6 entrance B	Link
Tutorial
Danielle Martin	06.09.23 – 06.12.23	Wednesday	12:00 – 13:30	A103 in B6, 23–25	Link
João Areal Neto	07.09.23 – 07.12.23	Thursday	15:30 – 17:00	A102, B6, 23–25	Link

ECTS

Course Type: elective course

Course Number: MET

Course Content

SMiP courses open to CDSS doctoral students

Please register online by 19 August 2023 and check the SMiP pages for continuous updates.

MET: SMiP Foundations of Statistical Modeling (CDSS only)

MET/POL: Advanced Topics in Comparative Politics: Formal Models in CP (and some in IR)

Lecturer(s)

Thorsten Meiser

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.

Block 1:	Dates: 19 October (10:00 a.m.- 6:00 p.m.) and 20 October 2023 (9:00 a.m. – 5.00 p.m.) Location: Mannheim (Room: 108 CIP Pool, B6 30-32)
Block 2:	Dates: 09 November (10:00 a.m.- 6:00 p.m.) and 10 November 2023 (9:00 a.m. – 5.00 p.m.) Location: Mannheim (Room: 108 CIP Pool, B6 30-32)
Block 3:	Dates: 11 January (10:00 a.m.- 6:00 p.m.) and 12 January 2024 (9:00 a.m. – 5.00 p.m.) Location: Mannheim (Room: 108 CIP Pool, B6 30-32)

Block 1:

Dates: 19 October (10:00 a.m.- 6:00 p.m.) and

20 October 2023 (9:00 a.m. – 5.00 p.m.)

Location: Mannheim (Room: 108 CIP Pool, B6 30-32)

Block 2:

Dates: 09 November (10:00 a.m.- 6:00 p.m.) and

10 November 2023 (9:00 a.m. – 5.00 p.m.)

Location: Mannheim (Room: 108 CIP Pool, B6 30-32)

Block 3:

Dates: 11 January (10:00 a.m.- 6:00 p.m.) and

12 January 2024 (9:00 a.m. – 5.00 p.m.)

Location: Mannheim (Room: 108 CIP Pool, B6 30-32)

Please register online by 19 August 2023 and check the SMiP pages for continuous updates.

CDSS doctoral students in psychology only who attend all three modules of this course can:

- let it count against the mandatory course Mathematics for Social Scientists (2 ECTS) and have 4 ECTS credited towards elective requirements in the MET module.

- let it count against the core course 'Theory Building and Causal Inference' (6ECTS), which is taught in spring.

Please contact the CDSS Center Manager to discuss the above mentioned possibilities.

MET/POL: Game Theory (Theory + Tutorial)

Lecturer(s)

Thomas Bräuninger

Course Type: elective course

Course Number: MET/POL

Credits: 10

Prerequisites

Topics covered in introductory Game Theory class

Course Content

This course is a continuation of the intro into Game Theory and surveys key applications of game theory with a particular emphasis on the link of theories, methods and empirics. Emphasis will be placed on prominent applications of those concepts in political science, in both comparative and international politics. Topics covered include electoral competition, delegation, political agency, governmental veto players, authoritarian politics, manipulation, war and crisis bargaining. While the focus is on understanding applied work, previous training in game theory is required. Students will build upon their previous game theory training to become informed consumers of scholarship utilizing the methodology and begin to learn how to apply game-theoretic logic to their own work. The course is partly taught from lecture notes, at other times students present a research paper and stimulate discussion in class.

Course requirements & assessment

Class discussion, paper presentation, participation, term paper (graded)

Literature

Various chapters of Scott Gehlbach's Formal Models of Domestic Politics (CUP) and journal articles from different fields

Schedule

Lecture
	05.09.23 – 05.12.23	Tuesday	13:45 – 15:15	C112 in A5, 6 entrance C

MET/PSY: Creating Experiments with lab.js

Lecturer(s)

Thomas Bräuninger

Carlos Gueiros

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

McCarty, Nolan and Adam Meirowitz. 2007. Political Game Theory. Cambridge: Cambridge University Press.
Tadelis, Steven. 2013. Game Theory: An Introduction. Princeton: Princeton University Press.
Osborne, Martin. 2003. An Introduction to Game Theory. Oxford: Oxford University Press.
Morrow, James. 1994. Game Theory for Political Scientists. Princeton, NJ: Princeton University Press.
Dixit, Avinash K., Susan Skeath, and David H. Reiley. 2009. Games of Strategy. 3. ed. New York: Norton.
Hinich, Melvin J. and Michael C. Munger. 1997. Analytical Politics. Cambridge: Cambridge University Press.
Osborne, Martin and Ariel Rubinstein. 2020. Models in Microeconomic Theory. Open Book Publishers.

Course requirements & assessment

Working in small groups on the assignments, online meetings on Zoom in groups, final exam (graded)

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
	04.09.23 – 04.12.23	Monday	10:15 – 11:45	C217 in A5, 6 entrance C
Tutorial
	08.09.23 – 08.12.23	Friday	12:00 – 13:30	C217 in A5, 6 entrance C

RES (Bridge course): Lecture series “Data Science in Action”

Course Type: elective course

Course Number: MET/PSY

Credits: 4

Course Content

lab.js is a simple, graphical tool to help you build studies for the web and the laboratory – in addition, it is free and open-source. Many standard tasks can be implemented in lab.js using its graphical user interface. Further, more complex tasks can be realized through the underlying programming language JavaScript.

The goal of the workshop is to provide an introduction to both approaches. In doing so, the workshop involves both structured input from the instructor as well as a number of practical exercises so that participants can directly explore the features of lab.js.

No prior knowledge of the software or JavaScript is required. As an assignment, participants will create their own experiment based on the requirements discussed in the workshop.

Course requirements & assessment

Participation; homework assignment in workshop break. As an assignment (graded), participants will create their own experiment based on the requirements discussed in the workshop.

Schedule

Seminar
	15.09.23	Friday	10:15 – 15:15	108 CIP-Pool in B6, 30–32	Link
	16.09.23	Saturday	10:15 – 17:00	108 CIP-Pool in B6, 30–32
	13.10.23	Friday	10:15 – 15:15	108 CIP-Pool in B6, 30–32
	14.10.23	Saturday	10:15 – 17:00	108 CIP-Pool in B6, 30–32

5 ECTS

Course Type: elective course

Course Number: RES (Bridge course)

Credits: 5

Course Content

Our colleagues from the Mannheim Center for Data Science are offering a lecture series “Data Science in Action” for the upcoming fall term. The lecture series is online and starts on Thursday, 14 September 2023 at midday.

GESS doctoral students can attend the event as a bridge course. In order to receive the 5 ECTS points, you need to take part in at 80% of the lectures and write a 15 page essay (pass/fail assessment).

For more information and registration, please visit the website:
https://www.uni-mannheim.de/en/datascience/details/vortragsreihe-data-science-in-action/

SOC: Advanced Topics in Education & Migration: Educational Inequalities in Europe

SOC: Muslim Immigration and Integration

Lecturer(s)

Reinhard Pollak

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. Education is associated with higher income, better health, more social contacts, less unemployment, more political engagement, and many more. In light of technological changes and the expansion of knowledge-based tasks, education might increase its importance even more. Yet, educational opportunities are still 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. And inequalities of educational opportunities do 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. Term paper (max. 5000 words, graded) Deadline: 21 January 2024

Schedule

Seminar
The Seminar will be held at GESIS	13.09.23	Wednesday	08:30 – 11:45	B6, 4–5 room 237	Link
	27.09.23	Wednesday	08:30 – 11:45	B6, 4–5 room 237
	04.10.23	Wednesday	08:30 – 11:45	B6, 4–5 room 237
	18.10.23	Wednesday	08:30 – 11:45	B6, 4–5 room 237
	08.11.23	Wednesday	08:30 – 11:45	B6, 4–5 room 237
	22.11.23	Wednesday	08:30 – 11:45	B6, 4–5 room 237
	29.11.23	Wednesday	08:30 – 11:45	B6, 4–5 room 237

SOC: Social stratification, social inequality and social mobility

Lecturer(s)

Marc Helbling

Course Type: elective course

Course Number: SOC

Credits: 6

Course Content

Up to the mid-1980s immigration was one of the least politicized issues on the political agenda of European countries. Since then, however, it has become one of the most important topics on the political agenda. Mass immigration has resulted in widespread xenophobia and fierce debates on the difficulties of integrating new arrivals. Muslim migration in particular seems to pose a special challenge to Western Europe, leading to widespread Islamophobia throughout the region. In this seminar we will consider reactions to Muslim immigration in Western Europe at various levels. What kind of policies do the European states implement in order to regulate mass immigration and integration? How do nationals react to this and how can we explain Islamophobia?

Course requirements & assignments

Participation, weekly reading, presentation of an empirical study, term paper (graded)

Schedule

Seminar
	06.09.23 – 06.12.23	Wednesday	10:15 – 11:45	A102, in B6 23-25

Dissertation Tutorial: Political Science

Lecturer(s)

Christof Wolf

Course Type: elective course

Course Number: SOC

Credits: 6

Prerequisites

Knowledge of basic concepts and theoretical models in sociology, in particular in the field of social stratification and social inequality, is beneficial. In addition sound methodological competencies are advantageous.

Course Content

Social stratification and inequality are universal characteristics of human societies. But the extent of inequality, the relevant dimensions of inequality and their interconnectedness vary across societies and through time. The course covers core aspects of social stratification and inequality in modern societies.
Objectives: In this course you will learn how social stratification, social inequality and social mobility shape Western societies. You will be introduced to the main dimensions of social inequality and processes by which social inequality is (re-)produced but also transformed. Through your course work, your presentation and your term paper you will gain experience in writing scientific texts and presenting scientific results.

Organization: During each session topics will be introduced by the instructor and then specific aspects will be highlighted in presentations by students (see dates below). Topics for presentations can be arranged with the instructor either before the start of the course via e-mail or at the first session.

Course requirements & assessment

It is assumed that all participants read the literature marked by an asterisk (*), actively follow the course, engage in discussions and do a presentation. The term paper should not exceed 5,000 words and should be delivered electronically via e-mail preferably in pdf-format to the instructor.

Deadline for delivery of the term paper is midnight January 31, 2024.

Dates and topics

15.09. Introduction
01        Introduction to topic and organization of the course
02        Social stratification and social inequality (Wehler 2013)

20.10. Conception of social inequality I
03        Classes, strata, lifestyles and milieus
04        Social classes and strata (* Sørensen 1994)

27.10. Conception of social inequality II
05        Horizont inequalities (* Deere/Kanbur/Stewart 2018)
06        Lifestyles and social milieus (* Sullivan 2012)

03.11. Education
07        Education 1: Empirical findings, theoretical reflections
(* OECD 2016: Indicator A1 and A4)
08        Education 2: Transitions in the educational system and to work (* Erikson/Rudolphi 2010; Smith/Crosnoe/Shih-Yi 2016; Barbieri/Cutuli/Passaretta 2018)

10.11. Income and Poverty
09        Educational effects on earnings (Johnes/Johnes/López-Torres 2017)
Income and wealth (Fessler/Schürz 2015)
10        Conceptualizing poverty and social exclusion in Europe (Aylló/Gábos 2017)

24.11. Social mobility and status attainment I
11        Social mobility: Evidence for Germany (* Müller/Pollack 2004)
12        Social mobility: European and international perspectives
(Breen/Luijkx 2004; * Nybom 2018)

01.12. Social mobility and status attainment II
13        The process of status attainment (* Yaish/Andersen 2012)
14        Final discussion

References

Ayllón, S., & Gábos, A. (2017). The Interrelationships between the Europe 2020 Poverty and Social Exclusion Indicators. Social Indicators Research, 130, 1025-1049. doi:10.1007/s11205-015-1212-2
Barbieri, P., Cutuli, G., & Passaretta, G. (2018). Institutions and the school-to-work transition: disentangling the role of the macro-institutional context. Socio-Economic Review, 16(1), 161–183. doi:10.1093/ser/mww019
Becker, G. S., Kominers, S. D., Murphy, K. M., & Spenkuch, J. L. (2018). A theory of intergenerational mobility. Journal of Political Economy, 126(S1), S7-S25.
Breen, Richard and Ruud Luijkx. 2004. Social mobility in Europe between 1970 and 2000. Pp.. 37–75 in: R. Breen (Ed.): Social Mobility in Europe. Oxford: Oxford University Press.
Deere, C. D., Kanbur, R., & Stewart, F. (2018). Horizontal inequalities. In J. E. Stiglitz, J.-P. Fitoussi, & M. Durand (Eds.), For Good Measure. Advancing research on well-being metrics beyond GDP: OECD.
Erikson, Robert and Frida Rudolphi. 2010. Change in social selection to upper secondary school – primary and secondary effects in Sweden. European Sociological Review, 26(3), 291–305.
Fessler, P., & Schürz, M. (2015). Private wealth across European countries: the role of income, inheritance and the welfare state. In E. C. B. W. P. 1847 (Ed.): European Central Bank.
Johnes, G., Johnes, J., & López-Torres, L. (2017). Human capital and returns to education. In G. Johnes, J. Johnes, T. Agasisti, & L. Lopez-Torres (Eds.), Handbook of contemporary education economics (2 ed.): Edgar Elgar.
Müller, Walter and Reinhard Pollak. 2004. Social mobility in West Germany: The long arms of history discovered? Pp. 77–114 in: R. Breen (ed.). Social Mobility in Europe. Oxford: Oxford University Press.
Nybom, M. (2018). Intergenerational mobility: A dream deferred? Geneva: International Labour Office.
OECD. 2016. Education at a Glance 2016. OECD indicators. Paris: OECD Publishing.
Sørensen, Aage. 1994. The basic concepts of stratification research: Class, Status, and Power. Pp. 229–241 in: D. B. Grusky (Ed.), Social Stratification. Class, Race, and Gender in Sociological Perspective. Boulder: Westview.
Smith, C., Crosnoe, R., & Shih-Yi, C. (2016). Family background and contemporary changes in young adults’school-work transitions and family formation in the United States. Research in Social Stratification and Mobility, 46, 3–10. doi:http://dx.doi.org/10.1016/j.rssm.2016.01.006
Sullivan, Alice. 2012. The Intergenerational Transmission of Lifestyles. Kölner Zeitschrift für Soziologie und Sozialpsychologie 51 (Special Issue):196–222.
Wehler, Hans-Ulrich. 2013. Die neue Umverteilung. Soziale Ungleichheit in Deutschland. München: C.H. Beck.
Yaish, Meir and Robert Andersen. 2012. Social mobility in 20 modern societies: The role of economic and political context. Social Science Research 41:527–238.

Schedule

Seminar
	15.09.23	Friday	10:15 – 13:30	B317 in A5, 6 entrance B	Link
	20.10.23	Friday	10:15 – 13:30	B317 in A5, 6 entrance B
	27.10.23	Friday	10:15 – 13:30	B317 in A5, 6 entrance B
	03.11.23	Friday	10:15 – 13:30	B317 in A5, 6 entrance B
	10.11.23	Friday	10:15 – 13:30	B317 in A5, 6 entrance B
	24.11.23	Friday	10:15 – 13:30	B317 in A5, 6 entrance B
	01.12.23	Friday	10:15 – 13:30	B317 in A5, 6 entrance B

0 ECTS

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

BAS: Mathematics for Social Scientists

Lecturer(s)

Thomas Gschwend

Course Type: core course

Course Number: BAS

Credits: 2

Course Content

Talk schedule

Schedule

Lecture
	08.09.23	Friday	12:00 – 15:15	Online	Link
	11.09.23	Monday	12:00 – 15:15	online
	18.09.23	Monday	12:00 – 15:15	online

MET: Crafting Social Science Research

Lecturer(s)

Emre Can Oral

Course Type: core course

Course Number: BAS

Credits: 2

Course Content

The exam is scheduled for tbc

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

Workshop
biweekly	13.09.23 – 06.12.23	Wednesday	13:45 – 17:00	211 in B6, 30–32	Link

MET: Quantitative Methods (formerly Multivariate Analyses (Theory + Lab Course))

Lecturer(s)

Thomas Gschwend

Course Type: core course

Course Number: MET

Credits: 6

Course Content

Course requirements & assessment

Schedule

Workshop
	05.09.23 – 05.12.23	Tuesday	10:15 – 11:45	211 in B6, 30–32	Link

MET/POL: Game Theory (Theory + Tutorial)

Lecturer(s)

Thomas Gschwend

Course Type: core course

Course Number: MET

Credits: 6 + 2

Course Content

Course requirements & assessment

Homework, participation, take-home exam (graded)

Schedule

Lecture
	06.09.23 – 06.12.23	Wednesday	08:30 – 10:00	B 244 in A5,6	Link
	02.11.23	Thursday	08:30 – 10:00	B 244 in A5, 6 entrance B
Tutorial
Oliver Rittmann	07.09.23 – 07.12.23	Thursday	10:15 – 11:45	310 in B6, 30–32	Link
Domantas Undzenas	08.09.23 – 08.12.23	Friday	10:15 – 11:45	A102 in B6, 23–25	Link

RES: CDSS Workshop: Political Science

Lecturer(s)

Thomas Bräuninger

Carlos Gueiros

Course Type: core course

Course Number: MET/POL

Credits: 6 + 2

Course Content

McCarty, Nolan and Adam Meirowitz. 2007. Political Game Theory. Cambridge: Cambridge University Press.
Tadelis, Steven. 2013. Game Theory: An Introduction. Princeton: Princeton University Press.
Osborne, Martin. 2003. An Introduction to Game Theory. Oxford: Oxford University Press.
Morrow, James. 1994. Game Theory for Political Scientists. Princeton, NJ: Princeton University Press.
Dixit, Avinash K., Susan Skeath, and David H. Reiley. 2009. Games of Strategy. 3. ed. New York: Norton.
Hinich, Melvin J. and Michael C. Munger. 1997. Analytical Politics. Cambridge: Cambridge University Press.
Osborne, Martin and Ariel Rubinstein. 2020. Models in Microeconomic Theory. Open Book Publishers.

Course requirements & assessment

Working in small groups on the assignments, online meetings on Zoom in groups, final exam (graded)

Tutorial

Schedule

Lecture
	04.09.23 – 04.12.23	Monday	10:15 – 11:45	C217 in A5, 6 entrance C
Tutorial
	08.09.23 – 08.12.23	Friday	12:00 – 13:30	C217 in A5, 6 entrance C

Lecturer(s)

Thomas Bräuninger

Course Type: core course

Course Number: RES

Credits: 2

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) 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
	04.09.23 – 04.12.23	Monday	15:30 – 17:00	C 112 in A5, 6 entrance C	Link

RES: Colloquia

MET: Bayesian Statistics in the Social Sciences

Course Type: core course

Course Number: RES

Credits: 2

Course Content

CDSS doctoral students in political science and sociology can choose freely which weekly colloquium to attend. Colloquia must be attended regularly in year two and three of doctoral studies.

Please choose from

MZES A Colloquium “European Societies and their Integration”

MZES Colloquium B “European Political Systems and their Integration”

Please refer to the MZES webpage for all further details. The talk announcements will be communicated via the CDSS mailing list as well.

Alternatively you can attend the Mannheim Research Colloquium on Survey Methods (MaRCS), which will be announced through the Faculty of Social Sciences mailing list.

All 2nd and 3rd year students must hand in a list of colloquia attended in that semester to receive the 2 ECTS. As with any other course, an attandance of at least 80% of the courses is required.

MET: Cross Sectional Data Analysis (Lecture + Tutorial)

Course Type: elective course

Course Number: MET

Credits: 6

Prerequisites

Knowledge of statistics and empirical social research methods

Course Content

Course taught by Prof. Joe Sakshaug.

Learning outcomes: Upon completion of the module, students are able to:

Course requirements & assessment

The course is evaluated as 'pass/fail'.

Schedule

Seminar
	08.09.23 – 08.12.23	Friday	08:30 – 10:00	Online

MET: Research Design (Lecture + Tutorial)

Lecturer(s)

Thomas Gautschi

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

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
	05.09.23 – 05.12.23	Tuesday	13:45 – 15:15	A 103 in B6, 23–25	Link
Tutorial
Danielle Martin	05.09.23 – 05.12.23	Tuesday	15:30 – 17:00	D002 in B6, 27–29
Sandra Morgenstern	07.09.23 – 07.12.23	Thursday	12:00 – 13:30	B318, in A5, 6 entrance B

MET: SMiP – Research Training Group 'Statistical Modeling in Psychology' additional courses (CDSS only)

Course Type: elective course

Course Number: MET

Credits: 6 + 3

Course Content

Tutorial

Course requirements & assessment

Lecture: Participation, written exam (graded)
Tutorial: Homework, oral participation, presentation

The course will be taught by Nan Zhang, PhD

Schedule

Lecture
	07.09.23 – 07.12.23	Thursday	10:15 – 11:45	B143, in A5, 6 entrance B	Link
Tutorial
Danielle Martin	06.09.23 – 06.12.23	Wednesday	12:00 – 13:30	A103 in B6, 23–25	Link
João Areal Neto	07.09.23 – 07.12.23	Thursday	15:30 – 17:00	A102, B6, 23–25	Link

ECTS

Course Type: elective course

Course Number: MET

Course Content

SMiP courses open to CDSS doctoral students

Please register online by 19 August 2023 and check the SMiP pages for continuous updates.

MET: SMiP Foundations of Statistical Modeling (CDSS only)

MET/POL: Advanced Topics in Comparative Politics: Formal Models in CP (and some in IR)

Lecturer(s)

Thorsten Meiser

Course Type: elective course

Course Number: MET

Credits: 6

Course Content

Block 1:	Dates: 19 October (10:00 a.m.- 6:00 p.m.) and 20 October 2023 (9:00 a.m. – 5.00 p.m.) Location: Mannheim (Room: 108 CIP Pool, B6 30-32)
Block 2:	Dates: 09 November (10:00 a.m.- 6:00 p.m.) and 10 November 2023 (9:00 a.m. – 5.00 p.m.) Location: Mannheim (Room: 108 CIP Pool, B6 30-32)
Block 3:	Dates: 11 January (10:00 a.m.- 6:00 p.m.) and 12 January 2024 (9:00 a.m. – 5.00 p.m.) Location: Mannheim (Room: 108 CIP Pool, B6 30-32)

Block 1:

Dates: 19 October (10:00 a.m.- 6:00 p.m.) and

20 October 2023 (9:00 a.m. – 5.00 p.m.)

Location: Mannheim (Room: 108 CIP Pool, B6 30-32)

Block 2:

Dates: 09 November (10:00 a.m.- 6:00 p.m.) and

10 November 2023 (9:00 a.m. – 5.00 p.m.)

Location: Mannheim (Room: 108 CIP Pool, B6 30-32)

Block 3:

Dates: 11 January (10:00 a.m.- 6:00 p.m.) and

12 January 2024 (9:00 a.m. – 5.00 p.m.)

Location: Mannheim (Room: 108 CIP Pool, B6 30-32)

Please register online by 19 August 2023 and check the SMiP pages for continuous updates.

CDSS doctoral students in psychology only who attend all three modules of this course can:

- let it count against the mandatory course Mathematics for Social Scientists (2 ECTS) and have 4 ECTS credited towards elective requirements in the MET module.

- let it count against the core course 'Theory Building and Causal Inference' (6ECTS), which is taught in spring.

Please contact the CDSS Center Manager to discuss the above mentioned possibilities.

MET/PSY: Creating Experiments with lab.js

Lecturer(s)

Thomas Bräuninger

Course Type: elective course

Course Number: MET/POL

Credits: 10

Prerequisites

Topics covered in introductory Game Theory class

Course Content

Course requirements & assessment

Class discussion, paper presentation, participation, term paper (graded)

Literature

Various chapters of Scott Gehlbach's Formal Models of Domestic Politics (CUP) and journal articles from different fields

Schedule

Lecture
	05.09.23 – 05.12.23	Tuesday	13:45 – 15:15	C112 in A5, 6 entrance C

POL: Advanced Topics in Comparative Politics: Coalition politics

Course Type: elective course

Course Number: MET/PSY

Credits: 4

Course Content

Course requirements & assessment

Participation; homework assignment in workshop break. As an assignment (graded), participants will create their own experiment based on the requirements discussed in the workshop.

Schedule

Seminar
	15.09.23	Friday	10:15 – 15:15	108 CIP-Pool in B6, 30–32	Link
	16.09.23	Saturday	10:15 – 17:00	108 CIP-Pool in B6, 30–32
	13.10.23	Friday	10:15 – 15:15	108 CIP-Pool in B6, 30–32
	14.10.23	Saturday	10:15 – 17:00	108 CIP-Pool in B6, 30–32

POL: Advanced Topics in Comparative Politics: Free Speech and Censorship

Lecturer(s)

Marc Debus

Course Type: elective course

Course Number: POL

Credits: 10

Course Content

The way how parties agree to form stable multi-party cabinets is a key topic in the analysis of comparative politics. The recent rise in fragmentation of party systems in many countries puts coalition politics at the forefront. The recent success of left-wing and right-wing extremist and populist parties, often considered pariah parties, result in more complex government formation processes. Furthermore, the stability of coalitions is likely to decrease since recently formed coalitions tend to be ideologically more heterogeneous. Scientific interest in minority governments has also increased accordingly.
The seminar addresses questions of coalition politics in the full life cycle such as coalition bargaining, coalition formation, the role of coalition agreements, portfolio allocation, governing in coalitions, coalition committees, the role of prime ministers or head of states, and coalition termination.

Course requirements & assessment

Active participation, oral presentation on a research topic, term paper (graded, 15–20 pages)

Schedule

Seminar
	05.09.23 – 05.12.23	Tuesday	13:45 – 15:15	B317 in A5, 6 entrance B

POL: Advanced Topics in Comparative Politics: Political Behavior in Context

Lecturer(s)

Richard Traunmüller

Course Type: elective course

Course Number: POL

Credits: 10

Course Content

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 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
	07.09.23 – 07.12.23	Thursday	08:30 – 10:00	B318 in A5, 6 entrance B	Link

POL: Advanced Topics in International Politics: Populism, Technocracism, and Democracy

Lecturer(s)

Harald Schoen

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 conceptual and 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 empirical studies in the field and prepare research papers in which they analyze specific questions using available data sets.

Course requirements & assessment

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

Schedule

Seminar
	07.09.23 – 07.12.23	Thursday	13:45 – 15:15	B318 in A5, 6 entrance B	Link

RES (Bridge course): Lecture series “Data Science in Action”

Lecturer(s)

Thomas König

Course Type: elective course

Course Number: POL

Credits: 10

Course Content

Compared to the relationship between populism and democracy, little is known about the relationship between technocracism and democracy, while a lacuna exists about the relationship between populism and technocracism. In this seminar, participants will present two studies, one of each type, and develop own thoughts about their relationship.

Course requirements & assessment

Active and regular participation is recommended, presentation of two studies, term paper (graded)

Schedule

Seminar
	05.09.23 – 05.12.23	Tuesday	12:00 – 13:30	C 112 in A5, 6 entrance C	Link

5 ECTS

Course Type: elective course

Course Number: RES (Bridge course)

Credits: 5

Course Content

BAS: Current Research Perspectives

BAS: Mathematics for Social Scientists

Lecturer(s)

Thomas Gschwend

Course Type: core course

Course Number: BAS

Credits: 2

Course Content

Talk schedule

Schedule

Lecture
	08.09.23	Friday	12:00 – 15:15	Online	Link
	11.09.23	Monday	12:00 – 15:15	online
	18.09.23	Monday	12:00 – 15:15	online

MET: Crafting Social Science Research

Lecturer(s)

Emre Can Oral

Course Type: core course

Course Number: BAS

Credits: 2

Course Content

The exam is scheduled for tbc

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

Workshop
biweekly	13.09.23 – 06.12.23	Wednesday	13:45 – 17:00	211 in B6, 30–32	Link

Lecturer(s)

Thomas Gschwend

Course Type: core course

Course Number: MET

Credits: 6

Course Content

Course requirements & assessment

Schedule

Workshop
	05.09.23 – 05.12.23	Tuesday	10:15 – 11:45	211 in B6, 30–32	Link

RES: AC2/BC3 Colloquia I

RES: CDSS Workshop: Research in Clinical Psychology

Lecturer(s)

Georg W. Alpers

Herbert Bless

Arndt Bröder

Oliver Dickhäuser

Jochen E. Gebauer

Beatrice G. Kuhlmann

Jutta Mata

Thorsten Meiser

Stefan Münzer

Sabine Sonnentag

Michaela Wänke

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.

All 2nd and 3rd year doctoral students must attend the colloquia in order to receive the 2 ECTS.

RES: CDSS Workshop: Research in Cognitive Psychology

Lecturer(s)

Georg W. Alpers

Course Type: core course

Course Number: RES

Credits: 2

Prerequisites

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.

Each spring term there will be a joint CDSS Workshop that all CDSS doctoral students of psychology attend. Each autumn term you will have the choice between three CDSS Workshops with a focus on either clinical, cognitive or social research.

Course Content

Research in Clinical Psychology: We invite CDSS 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 our discussion.

Literature: References will be given during the course.

Competences acquired

Improvement in research skills and communication of research results.

Schedule

Workshop
	07.09.23 – 07.12.23	Thursday	13:00 – 14:00	016–017 in L 13, 15–17	Link

RES: CDSS Workshop: Research in Social Cognition

Lecturer(s)

Arndt Bröder

Edgar Erdfelder

Course Type: core course

Course Number: RES

Credits: 2

Prerequisites

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.

Course Content

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
	04.09.23 – 04.12.23	Monday	15:30 – 17:00	211 in B6, 30–32	Link

MET: Bayesian Statistics in the Social Sciences

Lecturer(s)

Herbert Bless

Michaela Wänke

Course Type: core course

Course Number: RES

Credits: 2

Prerequisites

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.

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 doctoral 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

Schedule

Workshop
	04.09.23 – 04.12.23	Monday	10:15 – 11:45	B317 in A5, 6 entrance B	Link

MET: Cross Sectional Data Analysis (Lecture + Tutorial)

Course Type: elective course

Course Number: MET

Credits: 6

Prerequisites

Knowledge of statistics and empirical social research methods

Course Content

Course taught by Prof. Joe Sakshaug.

Learning outcomes: Upon completion of the module, students are able to:

Course requirements & assessment

The course is evaluated as 'pass/fail'.

Schedule

Seminar
	08.09.23 – 08.12.23	Friday	08:30 – 10:00	Online

MET: Quantitative Methods (formerly Multivariate Analyses (Theory + Lab Course))

Lecturer(s)

Thomas Gautschi

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

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
	05.09.23 – 05.12.23	Tuesday	13:45 – 15:15	A 103 in B6, 23–25	Link
Tutorial
Danielle Martin	05.09.23 – 05.12.23	Tuesday	15:30 – 17:00	D002 in B6, 27–29
Sandra Morgenstern	07.09.23 – 07.12.23	Thursday	12:00 – 13:30	B318, in A5, 6 entrance B

MET: Research Design (Lecture + Tutorial)

Lecturer(s)

Thomas Gschwend

Course Type: elective course

Course Number: MET

Credits: 6 + 2

Course Content

Course requirements & assessment

Homework, participation, take-home exam (graded)

Schedule

Lecture
	06.09.23 – 06.12.23	Wednesday	08:30 – 10:00	B 244 in A5,6	Link
	02.11.23	Thursday	08:30 – 10:00	B 244 in A5,6 entrance B
Tutorial
Oliver Rittmann	07.09.23 – 07.12.23	Thursday	10:15 – 11:45	310 in B6, 30–32	Link
Domantas Undzenas	08.09.23 – 08.12.23	Friday	10:15 – 11:45	A102 in B6, 23–25	Link

MET: SMiP – Research Training Group 'Statistical Modeling in Psychology' additional courses (CDSS only)

Course Type: elective course

Course Number: MET

Credits: 6 + 3

Course Content

Tutorial

Course requirements & assessment

Lecture: Participation, written exam (graded)
Tutorial: Homework, oral participation, presentation

The course will be taught by Nan Zhang, PhD

Schedule

Lecture
	07.09.23 – 07.12.23	Thursday	10:15 – 11:45	B143, in A5, 6 entrance B	Link
Tutorial
Danielle Martin	06.09.23 – 06.12.23	Wednesday	12:00 – 13:30	A103 in B6, 23–25	Link
João Areal Neto	07.09.23 – 07.12.23	Thursday	15:30 – 17:00	A102, B6, 23–25	Link

ECTS

Course Type: elective course

Course Number: MET

Course Content

SMiP courses open to CDSS doctoral students

Please register online by 19 August 2023 and check the SMiP pages for continuous updates.

MET: SMiP Foundations of Statistical Modeling (CDSS only)

MET/POL: Advanced Topics in Comparative Politics: Formal Models in CP (and some in IR)

Lecturer(s)

Thorsten Meiser

Course Type: elective course

Course Number: MET

Credits: 6

Course Content

Block 1:	Dates: 19 October (10:00 a.m.- 6:00 p.m.) and 20 October 2023 (9:00 a.m. – 5.00 p.m.) Location: Mannheim (Room: 108 CIP Pool, B6 30-32)
Block 2:	Dates: 09 November (10:00 a.m.- 6:00 p.m.) and 10 November 2023 (9:00 a.m. – 5.00 p.m.) Location: Mannheim (Room: 108 CIP Pool, B6 30-32)
Block 3:	Dates: 11 January (10:00 a.m.- 6:00 p.m.) and 12 January 2024 (9:00 a.m. – 5.00 p.m.) Location: Mannheim (Room: 108 CIP Pool, B6 30-32)

Block 1:

Dates: 19 October (10:00 a.m.- 6:00 p.m.) and

20 October 2023 (9:00 a.m. – 5.00 p.m.)

Location: Mannheim (Room: 108 CIP Pool, B6 30-32)

Block 2:

Dates: 09 November (10:00 a.m.- 6:00 p.m.) and

10 November 2023 (9:00 a.m. – 5.00 p.m.)

Location: Mannheim (Room: 108 CIP Pool, B6 30-32)

Block 3:

Dates: 11 January (10:00 a.m.- 6:00 p.m.) and

12 January 2024 (9:00 a.m. – 5.00 p.m.)

Location: Mannheim (Room: 108 CIP Pool, B6 30-32)

Please register online by 19 August 2023 and check the SMiP pages for continuous updates.

CDSS doctoral students in psychology only who attend all three modules of this course can:

- let it count against the mandatory course Mathematics for Social Scientists (2 ECTS) and have 4 ECTS credited towards elective requirements in the MET module.

- let it count against the core course 'Theory Building and Causal Inference' (6ECTS), which is taught in spring.

Please contact the CDSS Center Manager to discuss the above mentioned possibilities.

MET/POL: Game Theory (Theory + Tutorial)

Lecturer(s)

Thomas Bräuninger

Course Type: elective course

Course Number: MET/POL

Credits: 10

Prerequisites

Topics covered in introductory Game Theory class

Course Content

Course requirements & assessment

Class discussion, paper presentation, participation, term paper (graded)

Literature

Various chapters of Scott Gehlbach's Formal Models of Domestic Politics (CUP) and journal articles from different fields

Schedule

Lecture
	05.09.23 – 05.12.23	Tuesday	13:45 – 15:15	C112 in A5, 6 entrance C

MET/PSY: Creating Experiments with lab.js

Lecturer(s)

Thomas Bräuninger

Carlos Gueiros

Course Type: elective course

Course Number: MET/POL

Credits: 6 + 2

Course Content

McCarty, Nolan and Adam Meirowitz. 2007. Political Game Theory. Cambridge: Cambridge University Press.
Tadelis, Steven. 2013. Game Theory: An Introduction. Princeton: Princeton University Press.
Osborne, Martin. 2003. An Introduction to Game Theory. Oxford: Oxford University Press.
Morrow, James. 1994. Game Theory for Political Scientists. Princeton, NJ: Princeton University Press.
Dixit, Avinash K., Susan Skeath, and David H. Reiley. 2009. Games of Strategy. 3. ed. New York: Norton.
Hinich, Melvin J. and Michael C. Munger. 1997. Analytical Politics. Cambridge: Cambridge University Press.
Osborne, Martin and Ariel Rubinstein. 2020. Models in Microeconomic Theory. Open Book Publishers.

Course requirements & assessment

Working in small groups on the assignments, online meetings on Zoom in groups, final exam (graded)

Tutorial

Schedule

Lecture
	04.09.23 – 04.12.23	Monday	10:15 – 11:45	C217 in A5, 6 entrance C
Tutorial
	08.09.23 – 08.12.23	Friday	12:00 – 13:30	C217 in A5, 6 entrance C

MET/PSY: Psychological interventions using diary designs

Course Type: elective course

Course Number: MET/PSY

Credits: 4

Course Content

Course requirements & assessment

Participation; homework assignment in workshop break. As an assignment (graded), participants will create their own experiment based on the requirements discussed in the workshop.

Schedule

Seminar
	15.09.23	Friday	10:15 – 15:15	108 CIP-Pool in B6, 30–32	Link
	16.09.23	Saturday	10:15 – 17:00	108 CIP-Pool in B6, 30–32
	13.10.23	Friday	10:15 – 15:15	108 CIP-Pool in B6, 30–32
	14.10.23	Saturday	10:15 – 17:00	108 CIP-Pool in B6, 30–32

PSY: Advanced topics in Cognitive Psychology

Lecturer(s)

Sabine Sonnentag

Course Type: elective course

Course Number: MET/PSY

Credits: 4

Course Content

During recent years interventions using diary methods became increasingly popular within several fields of psychology, including health psychology and organizational psychology. These interventions use „intensive longitudinal designs“ to apply the treatment and to assess the data and build on daily-survey approaches that aim at „capturing life as it is lived” (Bolger, Davis, Rafaeli, 2003, p. 579). Frequent assessments typically implemented in daily-survey approaches allow for modeling change in affect, attitude, and behavior over time.
In this course we will discuss the nature of diary interventions, the research options they offer, as well as potential problems and challenges.

Literature (a more comprehensive list will be available in the first meeting)

Bolger, N., Davis, A., & Rafaeli, E. (2003). Diary methods: Capturing life as it is lived. Annual Review of Psychology, 54, 579–616.
Lischetzke, T., Reis, D., & Arndt, C. (2015). Data-analytic strategies for examining the effectiveness of daily interventions. Journal of Occupational and Organizational Psychology, 88, 587–622. doi:10.1111/joop.12104

Course requirements & assessment

Participation, presentation, term paper (graded)

Schedule

Seminar
	06.09.23 – 06.12.23	Wednesday	12:00 – 13:30	C112 in A5, 6 entrance C	Link

PSY: Advanced Topics in Work and Organizational Psychology

Lecturer(s)

Arndt Bröder

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)

Course requirements & assessment:

Active participation, final 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
	07.09.23 – 07.12.23	Thursday	15:30 – 17:00	B 144 in A5, 6	Link

PSY: Psychology of Creativity and Innovation

Lecturer(s)

Sabine Sonnentag

Course Type: elective course

Course Number: PSY

Credits: 4

Prerequisites

Knowledge in work and organizational psychology. It is expected that students know the content of a text book such as Spector (2008) or Landy & Conte (2010).

Course Content

This course provides an overview of core topics within work and organizational psychology. We will focus on recent theoretical approaches and empirical research findings (meta-analyses). In addition, we will discuss practical implications of core research findings. Topics include: Work motivation, stress and health, leadership, teams, personnel selection.

Methods comprise: Lecture, reading (as homework), teamwork assignments during class.

Course requirements and assessment
Graded homework assignment

Literature

Journal papers; reading assignments will be given at the beginning of the semester.

Schedule

Lecture
	07.09.23 – 07.12.23	Thursday	17:15 – 18:45	B244 in A5, 6 entrance B	Link