1. Learning Objectives – General learning outcomes

The main objective of this course is to provide to the students the opportunity to understand the basic principles and important methods of statistical analysis, necessary knowledge for understanding, amongst others, the demographic, socio-economic and spatial phenomena.

The course offers the opportunity to learn the procedures relative to the collect of data while emphasis is given to the interpretation and validity of the results (tests).

Upon the completion of the course, students will be able to collect appropriate data for the implementation of focused works and studies and better understand the usefulness of quantitative methods for (a) the analysis of socio -economic and spatial phenomena and (b) the decision-making process.

• Knowledge

At the end of the course, students are able to understand the main statistical methods for analyzing socio-economic phenomena that also have a spatial dimension. The course provides students with the opportunity to learn the processes of searching and collecting data while emphasis is given to the interpretation and reliability of the results.

• Skills

At the end of the course, students are able to use statistical methods for data analysis.

• Abilities

Upon completion of the course, students are able to seek appropriate data in order to implement studies as well as to better understand the usefulness of quantitative methods for (a) the analysis of socio-economic and spatial phenomena and (b) the effective decision-making process.

The course aims at the capability of searching, organizing and treatment of data and information in order to acquire the ability to implement scientific analysis as regards the organization of space at all scales (city-city-region).

Through the compulsory works, students acquire the ability to perform independent work and to develop critical thinking.

This is ensured by (i) the content of the lectures and (ii) the assignments / exercises given during the semester as well as (iii) the assessment’s system of the students.

The course consists of 13 lectures covering the most important fields of statistical analysis. More specifically, the course includes the following:

• Basic concepts, Contribution of Statistics to the scientific fields of Urban Planning, Spatial Planning and Regional Analysis, Useful Data Sources (ELSTAT, Eurostat etc)
• Data preparation, population / sample, variables / indicators (Examples of indicators: density index, siting index, etc.)
• Descriptive statistics: qualitative – quantitative variables, presentation of data, graphs.
• Exploratory analysis: central trend measures (simple and weighted average, median, quartiles, percentiles, Box-plot)
• Exploratory analysis: variance, standard deviation, coefficient of variation (CV, wCV), asymmetry
• Inference analysis: estimators, estimation by interval
• Inference analysis: Parametric tests (one sample-t test for mean value and proportion, independent samples t-test etc.).
• Correlation analysis (linear and non-linear) between quantitative variables
• Categorical data analysis: relationship between two qualitative variables, Chi-square test.
• ANOVA analysis
• Non-parametric tests
• Linear regression: simple and multiple, Excel applications

1. Short Answer Questions
2. Resolution of problems
3. Mandatory written assignments (5)
4. Intermediate exam
5. Final written exam

• The 5 mandatory written assignments (one every 15 days): 25%
• The Intermediate exam: 25%
• The final written examination: 50%

certify the students’ understanding of the basic concepts and the statistical methods presented throughout the semester.

The course outline explicitly mentions how students are evaluated and is available on the open e-class of the University of Thessaly.

Through meetings, students / students are able to systematically solve all possible questions during the semester. Students have access to special material which details the responses relative to the written assignments and the intermediate exam as well as how students have been evaluated.

Transparency is fully guaranteed. If there is a divergence of opinion regarding their final assessment, the students have the right to request upgrading from the General Department of the Department.

• Ιωαννίδης Δ. (2018), Στατιστικές Μέθοδοι, Θεωρία & εφαρμογές με χρήση Excel & R, Εκδ. Τζιόλα, ISBN: 978-960-418-761-4, (Εύδοξος: 77106795)
• Keller G. (2010), Στατιστική για οικονομικά και διοίκηση επιχειρήσεων, Εκδ. Επίκεντρο, ISBN: 978-960-458-206-8 , (Εύδοξος: 15310)
• Κολυβά-Μαχαίρα Φ., Μπόρα-Σέντα Ε., Μπράτσας Χ. (2018), Στατιστική: Θεωρία – Εφαρμογές – Παραδείγματα στην R, Εκδ. Ζήτη Πελαγία & Σια Ι.Κ.Ε., ΙSBN: 978-960-456-511-5, (Εύδοξος: 77120260)
• Detailed notes, small sheets relative to each one of the lesson’s chapters, resolution of important examples with interpretation of the results are also given and available on the Open e-class of the University.