Spatial Analysis of Elections

Course Information
TitleΧώρος και Εκλογική Ανάλυση / Spatial Analysis of Elections
FacultySocial and Economic Sciences
SchoolPolitical Sciences
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
CoordinatorIoannis Andreadis
Course ID100001145

Programme of Study: PPS Tmīma Politikṓn Epistīmṓn 2023-sīmera

Registered students: 0
OrientationAttendance TypeSemesterYearECTS
KORMOSElective CoursesSpring-4

Class Information
Academic Year2018 – 2019
Class PeriodSpring
Faculty Instructors
Weekly Hours3
Class ID
Course Type 2016-2020
  • Scientific Area
  • Skills Development
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
  • Distance learning
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Examination)
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.
Ecological inference, Thematic Maps
Educational Material Types
  • Notes
  • Interactive excersises
  • Book
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
Use of laptop and projector. The course is directly related to ICT. R, Ezi Mapinfo and spreadsheets are on everyday use.
Course Organization
Reading Assigment200.7
Interactive Teaching in Information Center150.5
Written assigments150.5
Student Assessment
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)
  • Labortatory Assignment (Formative, Summative)
Course Bibliography (Eudoxus)
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.
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