Syllabus
Title
5308 Research Seminar
Instructors
Julia Koschinsky, Ph.D.
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
02/13/14 to 02/28/14
Registration via LPIS
Registration via LPIS
Notes to the course
Subject(s) Doctoral/PhD Programs
Dates
| Day | Date | Time | Room |
|---|---|---|---|
| Tuesday | 03/18/14 | 02:30 PM - 04:00 PM | TC.3.09 |
| Tuesday | 03/25/14 | 02:30 PM - 05:30 PM | TC.5.18 |
| Friday | 05/02/14 | 02:00 PM - 05:00 PM | TC.3.12 |
| Friday | 05/09/14 | 02:00 PM - 05:00 PM | TC.3.12 |
| Friday | 05/16/14 | 02:00 PM - 05:00 PM | TC.3.12 |
| Friday | 05/23/14 | 02:00 PM - 05:00 PM | TC.3.12 |
| Friday | 05/30/14 | 02:00 PM - 05:00 PM | TC.3.12 |
| Friday | 06/06/14 | 02:00 PM - 05:00 PM | TC.3.12 |
The goal of this 8-week courseis to teach students foundational concepts in spatial analysis (exploratory andspatial modeling) and how to apply them in order to gain insights from spatialpatterns in your data. Students will use the free and opensource software programs GeoDa and GeoDaSpace on their own laptop (Windows or Mac). Students are encouragedto use your own research questions and data (e.g. related to theirdissertation) in this context. The spatial methods taught in this course are general enough (dealing with dependence between observations) in order to be applied to non-spatial data. The course will be taught inEnglish.
After completion of the course, students will understand the basic principles and concepts of spatial analysis and be able to apply available open source software to their own datasets and research questions.
The course will use a combination of readings, presentations and hands on application and training.
Students will be evaluated based on course participation, application of the methods to a practical example and presentation of research design and results.
Last edited: 2014-01-16
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