How to Make and Break Statistics (The Basics of Doing, Making and Reviewing Statistics) (Seminar)
|Language of instruction||English|
|Position within curricula||See TUMonline|
- 23.04.2019 16:15-17:45 270, Seminarraum
- 15.05.2019 16:15-17:45 270, Seminarraum
- 22.05.2019 16:15-17:45 270, Seminarraum
- 29.05.2019 16:15-17:45 270, Seminarraum
- 05.06.2019 16:15-17:45 270, Seminarraum
- 12.06.2019 16:15-17:45 270, Seminarraum
- 19.06.2019 16:15-17:45 270, Seminarraum
- 26.06.2019 16:15-17:45 270, Seminarraum
- 03.07.2019 16:15-17:45 270, Seminarraum
- 10.07.2019 16:15-17:45 270, Seminarraum
- 17.07.2019 16:15-17:45 270, Seminarraum
- 24.07.2019 16:15-17:45 270, Seminarraum
Course criteria & registration
Upon successful completion of this module the students are familiar with the basics of statistics: different perspectives, problems and capacities. They are able to evaluate socio-historic dependencies and impacts of applied statistics as well as their epistemological qualities and limits. They can identify appropriate strategies - according to the given contexts and objectives - to structure and draft controversial discussions and are able to offer constructive criticism on issues of statistics in contexts of responsibility at the intersection of science, technology, and society. Furthermore, the students are able to present issues of statistics to an audience.
This seminar focuses on basics of statistics for both: doing your own statistical research and critically discussing given statistical findings. We will look into (mathematical) basics, methods, strategies, history and epistemology of statistics. By means of presentations, readings, discussions and exercises we will explore the scientific capacities, limits, issues and risks of statistical work. Focusing on the intersection of science, technology and society in terms of responsibility, the seminar will have a rather socio-scientific and philosophical scope; however, in order to understand and constructively critize statistics (and do your own), we will take engineering and hard-science perspectives seriously and into account. The seminar will also repeatedly ask for an appropriate set of metaphysics: do statistics need to claim to be objective in order to be scientifically productive; do constructivists need to omit statistics? Beyond intrinsic questions of statistic qualities, the seminar will thus reflect on questions like: what is a good/constructive critique? What are good data? What are good findings? Can statistical knowledge production and construction of entities and populations be integrated in an educational, informative, neutral and especially responsible way?
Teaching and learning methods
Presentations by the instructors give students an introduction into the methodology and basics of statistics. Reading assignments and group discussions then train the students' ability to read, assess and discuss methodological strategies of statistics in the light of potential social and/or epistemological problems and controversies. The students prepare and hold presentations, produce texts, critique each other's work and use this feedback to revise their work in order to train their ability to structure and draft controversial discussions on issues of statistics, present them in front an audience and offer constructive criticism.
The examination requirement is a research paper accompanied by a presentation. The written work, which makes up 70% of the grade, discusses a selected issue (e.g. statistical report) to prove the students’ ability to discuss different perspectives on statistical findings, identify problems and strategies, structure and draft controversial discussions and offer constructive criticism on issues of statistics (30,0000 characters). The presentation deals with prerequisites and consequences of statistics in a case to be specified by the student (à 20 minutes). It is weighted 30% and proves that the students are able to present issues of statistics to an audience.
Heumann/Schomaker/Shalabh (2016): Introduction to Statistics and Data Analysis. Springer. Labovitz (1972): Statistical Usage in Sociology. Sacred Cows and Ritual; in: Sociological Methods & Research 1 (1). Sage. Engman (2013): Is there a life after P<0.05? Statistical significance and quantitative sociology; in: Quality & Quantity 47 (1). Springer.