Workshop: "Grundlagen Statistikpaket „R“" (29.09. & 30.09.2022, jeweils 9:00 bis 17:00 Uhr)

Inhalte:

Im Rahmen dieses Grundlagenmoduls soll eine Einführung in das Programmieren mit der Statistik-Software R vermittelt werden.

Das Kurs-Programm umfasst typische Aufgaben, die im Rahmen einer empirischen Untersuchung anfallen (Datenmanagement, deskriptive Statistik und schließende Statistik). Der Kurs wird durch einige Anwendungsbeispiele im Übungsformat abgerundet, die perspektivisch die Möglichkeiten von R aufzeigen. Durch eine Einführung in die ausführliche und umfassende Dokumentation zu R werden die Teilnehmer/innen befähigt, sich selbständig in spezifische R-Funktionen einzuarbeiten.

Ablauf:

• Einführung in die Benutzeroberfläche und grundlegende Befehle
• Erläuterungen zu Datenmanagement
• Deskriptive Statistik mit R (inkl. Grafiken)
• Schließende Statistik mit R (insbesondere Testen und Regression)
• Beispielhafte Anwendungen, Überblick über weitere Funktionen

Methode:

• Grundlagen und Codes werden in Themenblöcken von Dozenten vorab vermittelt
• Gemeinsames Evaluieren der Lerninhalte
• praktische Anwendung der vermittelte Inhalte (selbständiges Arbeiten)

Lernziele:

Eigenständiges Arbeiten und Vermittlung von Lösungsansätzen statistischer Problemstellungen mittels R

Voraussetzungen für die Teilnahme:

Kenntnisse der deskriptiven Statistik sowie der Inferenz­statistik (Testen, Regression) , keine Vorkenntnisse im Umgang mit R erforderlich

Maximale Teilnehmerzahl: 20 Personen

Zielgruppe: Promovierende/ Postdocs

Termin: Donnerstag, 29.09.2022, 9:00 bis 17:00 Uhr & Freitag, 30.09.2022, 9:00 bis 17:00 Uhr

Arbeitseinheiten: 16 AE

Ort: Raum RZ/01.02 - PC-Pool (Präsenzveranstaltung)

Leitung: Paul Messer, Marta Anzalone/ BACES

Anmeldung: Bitte melden Sie sich bis zum 15.09.2022 über dieses Formular an.

Workshop: "Modern Causal Analysis - Causal Inference Based on Non-experimental Data" (10.10. & 11.10.2022, 09:15 a.m. to 5:00 p.m. (s.t.))

This workshop is organised by BAGGS.

Description:

Causal inference is a central goal of quantitative empirical social research. In research practice, however, often only non-experimental data are available, which complicates the identification and estimation of causal effects due to non-random selection processes. Current empirical social research therefore increasingly applies methods of causal analysis to nonexperimental data that are based on a clear conception of causality and explicitly account for non-random selection processes.
This workshop introduces these methods. Based on the principles of theory-driven empirical social research, it first explains the idea of causal hypotheses and distinguishes the goal of causal inference from alternative goals. The counterfactual model of causality and causal graphs are introduced as the two most important conceptual foundations of various methods of causal inference. Furthermore, regression analysis is considered from a new causal perspective, and recent debates on the selection of control variables and causal model building as well as regression adjustment are discussed. In addition, (propensity score) matching, inverse probability weighting, instrumental variable estimators, and difference-in-differences estimators are presented from an applied research perspective.
Each method is described in terms of the underlying assumptions of causal identification and estimation, and potential trade-offs between internal and external validity. The methods will be practiced using the statistical program Stata on cross-sectional and longitudinal data for practical examples from sociological research.

The workshop is mainly aimed at doctoral candidates. In case of any vacant places, it is open to anyone interested.

Prerequisite Knowledge:

Participants are expected to be familiar with the basics of statistics and they should be familiar with multiple linear regression analysis. Empirical applications will be implemented in Stata. In support, prepared data sets and full syntax codes will be provided, but a basic knowledge of Stata is needed to run the practical examples independently.

Max. number of participants: 14

Date & time: Monday, October 10, 2022, 09:15 a.m. to 5:00 p.m. (s.t.) & Tuesday, October 11, 2022, 09:15 a.m. to 5:00 p.m. (s.t.)

Place: BAGSS, Feldkirchenstraße 21, 96052 Bamberg, Room FG1/00.06 & via Zoom

Consultant: Dr. Jonas Voßemer

Jonas Voßemer is a postdoctoral fellow at the Mannheim Centre for European Social Research (MZES) at the University of Mannheim. He graduated in sociology and economics from the University of Mannheim and received his doctoral degree in sociology from the University of Bamberg. In his research, he studies the interactions between labor markets, families, and health and well-being mostly using longitudinal survey data and applying methods of causal inference. His research is based on a sociological life course perspective and follows an international comparative approach.

Course units: 14

Registration: To register as a member of University of Bamberg, please use this form by September 09, 2022.

Online-Workshop: "Data Visualization with R" (02.11. & 04.11.2022, 09:00 a.m. to 12:00 p.m. (s.t.))

This workshop is organised by BAGGS.

Description:

The aim of the workshop is to provide an accessible introduction into the use of R for data visualization. R’s ggplot2 package and its extensions provide a flexible framework for data visualization and they are widely used in both academia and industry.

Topics:

• Data visualization basics (very briefly)
• Introduction to the most common plot types (barcharts, scatterplots, etc.)
• Introduction to some not-so-common plot types (maps, networks)
• How to visualize results of different research outputs
• Creating unique themes
• Programming with ggplot2

The workshop is practice-oriented, which means that we will have some smaller and bigger coding challenges to exercise the ggplot muscle memory early on. If you have your own dataset and are looking for ideas on possible ways to represent it, let me know and we can take a collective look at it.

Prerequisites:

• You should have a working R (version 4.0.0 +) and RStudio (version 1.4.+) installed.
• Basic familiarity with R is expected.
• Some statistical knowledge is also assumed (but not necessary), but if you have seen an OLS regression then you are good to go.

Preparation:

To refresh or solidify your skills in R, you can also cover the following introductory material provided by Ákos Máté:

• The free and online book R for Data Science, chapters 9 – 12

Date & time: Wednesday, November 02, 2022, 09:00 a.m. to 12:00 p.m. (s.t.) & Friday, November 04, 2022, 09:00 a.m. to 12:00 p.m. (s.t.)

Place: Virtual Workshop via Zoom

Consultant: Ákos Máté, Research Fellow, Center for Social Sciences, Budapest

Ákos Máté is a research fellow at the Centre for Social Sciences. His key research area is the political economy of the European Union and its members’ fiscal governance.
He uses a wide variety of methods in his research, particularly automated text analysis (and attached various machine learning approaches), network analysis and more traditional econometric techniques.

Course units: 8

Registration: To register as a member of University of Bamberg, please use this form by October 13, 2022.

Online-Workshop: "Multilevel Modeling - An Introduction" (09.12. & 12.12.2022, 10:00 a.m. to 5:00 p.m. (s.t.))

This workshop is organised by BAGGS.

Description:

This two-day online-workshop provides an overview of Multilevel Modeling, or MLM, the appropriate term for what many call hierarchical linear modeling. During the workshop Prof Nezlek will provide a rationale for using MLM, and will explain different aspects of MLM such as centering and modeling error terms. Step by step instructions for conducting multilevel analyses using the program HLM will be presented, and these instructions will be linked to data sets and program files that will be provided to participants. During the second day, you will discuss HLM analyses in more detail, and participants will be able to conduct analyses of their own data with the instructor’s assistance. If participants do not have their own data, they can analyze example data sets. During both days, how to prepare raw data for MLM analyses will be dis-cussed. Note: The HLM program runs only on Windows.

The workshop is mainly aimed at doctoral members of Bamberg Graduate School of Social Sciences and Leibniz Institute for Educational Trajectories. In case of any vacant places, it is open to anyone interested.

Prerequisites:

Participants should be familiar with OLS (ordinary least squares) regression analyses.

Max. number of participants: 16

Date & time: Friday, December 09, 2022, 10:00 a.m. to 05:00 p.m. (s.t.) & Monday, December 12, 2022, 10:00 a.m. to 05:00 p.m. (s.t.)

Place: Online Workshop via Zoom

Consultant: Prof Dr John B. Nezlek, SWPS University of Social Sciences and Humanities and the College of William & Mary

Prof Dr John B. Nezlek is a Professor at SWPS University of Social Sciences and Humanities in Warsaw and the College of William & Mary in Williamsburg, USA. His research interest are social and personality psychology. He has given dozens of MLM workshops worldwide and has published numerous article and chapters that use or describe MLM, including a chapter for the upcoming APA Handbook of Research Methods. He has also published two books about MLM: ‘Multilevel modeling for social and personality psychology’ and ‘Diary methods for social and personality psychology.’

Course units: 16

Registration: To register as a member of University of Bamberg, please use this form by October 28, 2022.

Workshop: "Wissenschaftliche Aufsätze schreiben – die eigene Forschung nachvollziehbar machen" (05.05.2023, 9:00 bis 17:00 Uhr)

Dieser Workshop wird in Kooperation mit dem Leibnitz Institut für Bildungsverläufe (LIfBI) angeboten.

Inhalte:

Wissenschaftliche Aufsätze sind ein fundamentaler Bestandteil der wissenschaftlichen Kommunikation. Artikel in Fachzeitschriften oder Sammelbänden sind der gängigste Weg, um die Fachcommunity über die eigene Forschung zu informieren. In dem Workshop lernen die Teilnehmenden, was zur Erstellung eines eigenen wissenschaftlichen Artikels dazugehört: von der Planung über das Schreiben des Abstracts und Hauptteils bis zum Überarbeitungsprozess. Die Arbeitssprache des Workshops ist deutsch.

Ablauf:

• Zweck wissenschaftlicher Artikel
• Planung des eigenen Artikels
• Titel und Abstract schreiben
• Die Struktur eines guten Artikels
• Sprachliche Gestaltung des Artikels
• Überarbeitung und Umgang mit Feedback

Methode:

Der Fokus des Workshops liegt auf praktischen Schreibübungen, die dabei helfen, den eigenen Artikel zu strukturieren und klar zu formulieren. Kurze Input-Sequenzen durch die Trainerin bereiten darauf vor. Außerdem werden in Kleingruppen Beispiele aus der Praxis diskutiert. Die Teilnehmenden sollen schon während des Workshops die Anregungen auf das eigene wissenschaftliche Vorhaben übertragen.

Lernziele:

• Die eigene Forschung für einen wissenschaftlichen Artikel aufbereiten
• Abstract als Planungstool verstehen
• Den Artikel sinnvoll strukturieren
• Treffende, klare Formulierungen finden
• Feedback richtig nutzen

Voraussetzungen für die Teilnahme: Idee für eigenen wissenschaftlichen Artikel

Maximale Teilnehmerzahl: 12 Personen

Zielgruppe: Promovierende der Geistes- und Sozialwisssenschaften

Termin: 05.05.2023, 9 s.t.– 17 Uhr (inkl. Pausen)

Arbeitseinheiten: 8 AE

Ort: WE5/04.003

Leitung: Alisa Müller, M.A.

Alisa Müller arbeitet in Nürnberg als Redakteurin und seit zehn Jahren als freie Journalistin für verschiedene Printmedien. Sie hat in der slavischen Sprachwissenschaft an der Universität Bamberg promoviert.

Anmeldung: Bitte melden Sie sich bis zum 21.04.2023 über dieses Formular an.