Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Marco Lehmann, UKE Hamburg

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (14.30–18.00 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The course introduces the programming language R used for statistical analyses. The beginning of each lecture comes with a demonstration of programming and statistical functions that will be elaborated in the course of study. The students will then practice with many statistical examples. In addition to statistical functions, the course will introduce the definition of R as a programming language and its syntax rules. Students will further learn to use R’s scripting capabilities. Successful participation requires basic knowledge in descriptive and inferential statistics. The students are encouraged to bring their own laptops with the free software R (www.r-project.org/) and RStudio (www.rstudio.com/) installed.

Requirement of students: Basic knowledge in descriptive and inferential statistics is recommended.

Recommended literature and pre-readings:

• Matloff, N. (2011). The Art of R Programming: A Tour of Statistical Software Design. No Starch Press.
• Wollschläger, Daniel (2012). Grundlagen der Datenauswertung mit R (2. Aufl.). Berlin: Springer.

You have to register for the 12th International Research Workshop to participate in this course.

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Jun.-Prof. Dr. Katharina Stornig, Justus-Liebig-Universität, Gießen and Dr. Paul Vickers, Universität Regensburg

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (09.00-12.30 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

All research, whatever the discipline and however original, draws on existing studies. Any research project necessarily positions itself in relation to existing empirical, theoretical and methodological debates. This course provides practical insight and advice on how to write a literature review (Forschungsstand) providing an overview of the “state of the art”. The course will begin with insights on tips, tricks and tactics for tackling the literature review, including collecting and synthesizing literature, summarizing existing debates, and providing advice on academic writing in English and German. The sessions will also involve group work and focused feedback on individual projects.

Requirement of students: Each participant sends at least one week in advance of the course an extended abstract (Exposé) of their research project.

Recommended literature and pre-readings:

• Patrick Dunleavy. How to Plan, Draft, Write and Finish a Doctoral Thesis or Dissertation. Palgrave: 2003.
• Jose L. Galvan. Writing Literature Reviews: A Guide for Students of the Social and Behavioral Sciences. University of Michigan: 2004.
• Ansgar Nünning/Roy Sommer, Hrsg. Handbuch Promotion. Forschung – Förderung – Finanzierung. Metzler: 2007.

You have to register for the 12th International Research Workshop to participate in this course.

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Raphael Heiberger, University of Bremen

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (09.00-12.30 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The rising prominence of social network analysis (SNA) has been mirrored in the development of specialized tools and computer programs for various kinds of networks. This general trend has been enhanced by the current data revolution. Innovative methods to study social networks are often developed in the R-framework. The workshop introduces various R-packages on SNA and enables participants to construct, analyze and visualize network data. First, we will concentrate on the different logic of each package in terms of graph initialization, their general advantages and disadvantages, and how to overcome those differences. After practising how to treat network data in R, we will focus on the utilization of a variety of network measures describing both actor positions and whole networks. Additionally, there exist many built-in algorithms for community detection and network evolution that can be easily applied after the first steps. After a short explanation of the mathematical and theoretical intuition of the concepts in question, we will apply them to multiple empirical examples.

Requirement of students: Experiences with R might be helpful but are not a requirement. The workshop uses RStudio as a development environment. Please install R and RStudio prior to the workshop. To install, follow these steps:

1. Download the R-installer from https://cran.r-project.org. Select and download the latest installer suitable to your operating system.
2. Run the installer. Default settings are fine.
3. Download RStudio https://www.rstudio.com/products/rstudio/download.
4. Once the installation of R has completed successfully (and not before), run the RStudio installer.
5. Open RStudio. It should open a window that looks similar to the image attached.
6. Install R packages required for the workshop. To do that just type in the console install.packages(’MYLIB’) where MYLIB is a placeholder for the various packages we will need, especially:
   igraph
   igraphdata
   statnet
   ergmharris
   intergraph
   reshape2
7. You can see if the package installation was successful by just loading a package
   with library(MYLIB). Note that there are no quotes now.

Recommended literature and pre-readings:

• Marin, Alexandra & Barry Wellman (2011): Social Network Analysis: An Introduction. In: John Scott & Peter J. Carrington (Eds.): Sage Handbook of Social Network Analysis. London/New Delhi: Sage, pp. 11-26.
• Hanneman, Robert A. & Mark Riddle (2011): Concepts and Measures for Basic Network Analysis. In: John Scott & Peter J. Carrington (Eds.): Sage Handbook of Social Network Analysis. London/New Delhi: Sage, pp. 340-370.

You have to register for the 12th International Research Workshop to participate in this course.

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Christine Moritz, Feldpartitur GmbH

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (09.00-12.30 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The key purpose of this workshop is to offer a comprehensive introduction to Grounded Theory and it is both, theoretically and practically, orientated. First, participants meet the so-called “essentials”: research design; data collection, open/axial/selective coding, categorizing, writing memos and theoretical sampling (the subjects theoretical sensitivity and generating theory will only be touched), then, second, examples might exercise and clarify these concepts. To assist participants to develop valuable and effective research practices, exemplars from current research projects will be assessed and critically reflected. In addition to your registration please submit a brief abstract (1-2 pp.) and answer following questions (en/ger):

• What is your current status (e.g. PhD student?)
• What is the focus of your interest in Grounded Theory?
• What sort of content and what feedback do you expect?

Requirement of students: Brief abstract answering the above-mentioned questions.

Recommended literature and pre-readings: None.

You have to register for the 12th International Research Workshop to participate in this course.

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Sarah Potthoff, Ruhr-University Bochum

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (09.00-12.30 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The purpose of this course is to familiarize participants with the basics of qualitative interviewing. The course introduces methodological and practical aspects of different forms of qualitative interviews like guided interviews, narrative interviews and focus groups. How are these different kinds of interviews different, what are their shared fundamentals, and what makes a good interview in which circumstance?

The course covers issues of research design, including the selection of research questions, methods, and sampling strategies. The participants will learn to conceptualize interview guidelines and to conduct interviews – guided as well as narrative interviews. In addition, frequent mistakes in conducting qualitative interviews and challenges of research ethics will be discussed.

Requirement of students: None.

Recommended literature and pre-readings: None.

You have to register for the 12th International Research Workshop to participate in this course.

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Tobias Gramlich, Hesse State Statistical Office

Date: Monday, 10/09/18 – Wednesday, 12/09/18 (09.00-12.30 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

Stata is a statistical program package widely used (not only) in the social and economic sciences; it is used for data management, statistical graphics and analysis of quantitative data. Statistical concepts will not be part of the course, so participants should have some very basic knowledge of statistics. The course should enable participants to prepare their data for analysis, perform adequate analysis using a statistical computer program and document these tasks to keep them reproducible.

For Beginners with no or very little Stata knowledge!

Course topics cover:

• “What You Type is What You Get”: Basic Stata Command syntax
• Getting (and Understanding) Help within Stata: Stata Built-in Help System
• Basic Data Management: Load and Save Stata Datasets, Generate and Manipulate Variables, Describe and Label Data and Variables, Perform Basic uni- and bivariate Analyses, Change the Structure of your Data
• Basic Stata Graphics: Scatterplot, Histogram, Bar Chart
• Working with “Do-” and “Log-” Files

Requirement of students: Statistical concepts will not be part of the course, so participants should have some very basic knowledge of statistics.

Recommended literature and pre-readings: None.

You have to register for the 12th International Research Workshop to participate in this course.