LEARNING OUTCOMES
After completing the course, the students will be able to:
- draw samples from lists or maps
- analyze spatial data using Descriptive and Inferential Statistics
- apply statistical analysis in a GIS environment (GIS)
- solve geographical problems using appropriate software
- understand and discuss scientific publications which involve statistical analysis
- select the appropriate method of spatial analysis according to the nature of the problem and the data properties
General Competences
- Search for, analysis and synthesis of data and information, with the use of the necessary technology
- Working independently
SYLLABUS
1. Basic concepts: types of data, organization and properties of geographical data
2. Geographical data and scales of measurement
3. Geographical data collection: primary and secondary data, methods for data collection, spatial sampling techniques
4. Description of geographical data: frequency distributions, crosstabulations, visualization, measures of central tendency and dispersion, geostatistical indices, exploratory spatial data analysis
5. Probability distributions, hypothesis testing, statistical tests: t, ANOVA, Χ2
6. Spatial patterns, point pattern analysis, mapping spatial clusters
7. Correlation analysis of quantitative and qualitative data, regression analysis, multiple regression, spatial autocorrelation indices, spatial regression
8. Introduction to multivariate methods for geographical data analysis (factor analysis cluster analysis, discriminant analysis)
STUDENT PERFORMANCE EVALUATION
Language of evaluation: Greek or English
Methods of evaluation:
- Final exam (50%) which includes open- ended questions and problem solving
- Mid-term exam (10%) which includes open- ended questions and problem solving
- Laboratory work (40%)
ATTACHED BIBLIOGRAPHY
Suggested bibliography:
In Greek:
1. Iliopoulou P. 2015. Spatial Anlaysis. [e-book] Athens Hellenic Academic Libraries Link (Heal Link). Available at http://hdl.handle.net/11419/2059
2. Koutsopoulos K. 2009. Essay on spatial analysis, Vol. I and II, Papassotiriou, Athens.
In English:
1. Fotheringham S.A., Brudson C. and Charlton M. 2000. Quantitative Geography-Perspectives on Spatial Data Analysis, London: SAGE Publications
2. O’ Sullivan D. and Unwin D.J. 2010. Geographic Information Analysis, John Wiley
3. Robinson G.M. 1998. Methods and Techniques in Human Geography, Wiley
4. Rogerson P.A. 2004. Statistical Methods for Geography, Sage Publications
5. Wong D. W. S. and Lee J. (2005). Statistical Analysis of Geographic Information with ArcView GIS and ArcGIS, Wiley.
Related academic journals:
1. Geographical Analysis, Wiley
2. Applied Spatial Analysis and Policy, Springer