Spatial Analysis of Elections
| Title | Χώρος και Εκλογική Ανάλυση / Spatial Analysis of Elections |
| Code | ΚΕ0Ε30 |
| Faculty | Social and Economic Sciences |
| School | Political Sciences |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Spring |
| Coordinator | Ioannis Andreadis |
| Common | Yes |
| Status | Active |
| Course ID | 100001145 |
Programme of Study: PPS Tmīma Politikṓn Epistīmṓn 2023-sīmera
Registered students: 0
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Elective Courses | Spring | - | 4 |
| Academic Year | 2023 – 2024 |
| Class Period | Spring |
| Faculty Instructors | |
| Weekly Hours | 3 |
| Total Hours | 39 |
| Class ID | 600231420
|
Course Type 2016-2020
- Scientific Area
- Skills Development
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
- Distance learning
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600231420
- At the Website of the School: https://www.polsci.auth.gr/course_polsci/%cf%87%cf%8e%cf%81%ce%bf%cf%82-%ce%ba%ce%b1%ce%b9-%ce%b5%ce%ba%ce%bb%ce%bf%ce%b3%ce%b9%ce%ba%ce%ae-%ce%b1%ce%
- eLearning (Moodle): https://elearning.auth.gr/course/view.php?id=6466
Language of Instruction
- Greek (Instruction, Examination)
- English (Examination)
Prerequisites
General Prerequisites
The course uses items that have been taught in the following courses: "Mathematics in political science: introduction", "Social Statistics", and "Quantitative methods of analysis in the social sciences." Students who wish to attend the course should have satisfactorily understand the syllabus of these courses. The course requires using a PC. Satisfactory knowledge of files management, use word processing software (e.g. MS Word) and spreadsheets (e.g. Excel), and the desire for learning new software is necessary.
Learning Outcomes
Objectives of the course is that students gain the following capabilities:
Ability to reach useful conclusions from the results of the elections.
Ability to present data and estimates on electoral maps.
Ability to present analysis of election results in publishable work.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Adapt to new situations
- Make decisions
- Work autonomously
- Work in an international context
- Work in an interdisciplinary team
- Generate new research ideas
- Be critical and self-critical
- Advance free, creative and causative thinking
Course Content (Syllabus)
The main focus of this course is on the ecological inference problem, i.e. statistical inference from aggregate data. The course covers the following subjects: Data preparation for ecological analysis. Choice of statistical and spatial unit. Techniques and methods of ecological inference for 2x2 tables. Method of bounds. Regression methods. King's method and relevant techniques. Introduction to Ezi. The ecological inference problem for RxC tables. Elements of electoral geography. Geographic information systems. Introduction to Mapinfo. Thematic maps and cluster analysis. Introduction to language R. Data treatment in language R. Ecological inference techniques in language R. Elements of academic writing.
Keywords
Ecological inference, Thematic Maps
Educational Material Types
- Notes
- Interactive excersises
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
- Use of ICT in Communication with Students
Description
Use of laptop and projector. The course is directly related to ICT. R, Ezi Mapinfo and spreadsheets are on everyday use.
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 25 | 0.9 | ✓ | ||
| Reading Assigment | 20 | 0.7 | ✓ | ||
| Tutorial | 15 | 0.5 | ✓ | ||
| Interactive Teaching in Information Center | 15 | 0.5 | ✓ | ✓ | |
| Project | 20 | 0.7 | ✓ | ✓ | |
| Written assigments | 15 | 0.5 | ✓ | ✓ | |
| Total | 110 | 4 |
Student Assessment
Description
The students know what they should include in their work. They are monitored during its preparation and constantly receive comments on how to improve it.
Student Assessment methods
- Written Assignment (Formative, Summative)
- Oral Exams (Formative, Summative)
- Labortatory Assignment (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
Ανδρεάδης, Ιωάννης (2020) Χώρος και Εκλογική Ανάλυση. Δωρεάν Ηλεκτρονικό Βοήθημα / Σημειώσεις
Κωδικός Βιβλίου στον Εύδοξο: 59304114
Additional bibliography for study
King, Gary. 1997. A solution to the ecological inference problem : Reconstructing individual behavior from aggregate data. Princeton, N.J.: Princeton University Press.
King, Gary, Martin Abba Tanner, and Ori Rosen. 2004. Ecological inference : New methodological strategies. Analytical methods for social research. Cambridge ; New York: Cambridge University Press.
Last Update
20-05-2024
