The proper organization of the research as well as the identification of problematic and working assumptions are a prerequisite for the scientific analysis of any social, cultural, spatial and economic phenomena.
The effective implementation of research methods is based on (i) specific principles and concepts, (ii) specific tools (collecting and organizing databases, sample, questionnaires, interviews) as well as (iii) tools and methods of exploiting and analyzing the data / information collected.
The course emphasizes empirical scientific research (either quantitative or qualitative) which, under the proper methodological design, ensures objective and quantitative measurements of the phenomena examined while allows the systematic test of work assumptions.
The study of social, economic and spatial phenomena and the exploration of the relationships between their various components as well as the “increasing pressure” as regards the adoption of rational policies require the development of theoretical and empirical approaches in which the above analyzes can be based. Therefore, a key issue is the acquisition of knowledge and skills on the basis of which students will be able to integrate theoretical approaches – theories with the data collected in the context of their scientific research.
The course aims:
to proven knowledge and understanding about the design of scientific research, methodology and research methods. Developing the knowledge and understanding sub-research objects offers at the same time the opportunity to expand their scientific horizons.
To acquire knowledge about the use of different statistical techniques and methods
to obtain, by systematically applying the relevant methods, the necessary capabilities to adapt to actual research processes especially as regards search, treatment and interpretation of reliable information. At the end of the course, students will be able to design and carry out, in real terms, a small-scale as well as a large-scale scientific research.
to develop their ability to critically analyze, evaluate and synthesize complex and multi-dimensional concepts
to promote the progress of the knowledge society and generating new research ideas
to promote free, creative and inductive thinking.
The course is organized according to the following topics:
The logical steps for conducting scientific research
Selection of appropriate information / data and consequently of methods and tools of analysis.
Conducting research focusing on specialized and complex issues requires understanding and familiarity with appropriate Research Methods.
The main course content includes the following sections:
Concepts, principles, significance and aims of scientific research
Formulation of problematic (research question) and working hypotheses
Design, steps of preparation and implementation of scientific research,
Methodology and tools selection: theoretical approach as well as presentation – analysis of already implemented research, comparative presentation of research with primary or secondary data, inventories or sample research;
Random Sampling and Sampling Techniques, Sampling Error, Sampling Method Selection, Sample Size and Structure, Supplementary Sample: Theory and Application Using Special Software
Questionnaire design according to the type of empirical research (quantitative – qualitative) and the type of interviews:
– Advantages and disadvantages of alternative forms of empirical research and interview categories
– Questionnaire structure: from basic sections to section-by-section questions, question categories (open, closed, mixed, multiple / hierarchical choices), variable coding, choice of scales, Likert scale utility.
Applying research: from theory to practice
– pilot and final research,
– procedures and methods for filling out questionnaires,
– preparation and completion of the Database,
– verification of the reliability of the collected data (fiability, reliability)
Statistical processing and presentation of data:
Descriptive statistical analysis with primary and secondary data, generation of indicators (correlation, variability, inequality, concentration and specialization).
Software application of statistical analysis to real data.
Contribution and implementation of conventional methods of Analysis Data / information
Exploratory empirical approaches of the relationships between variables with Principal Component Analysis (PCA), ‘measurement’ of multidimensional phenomena through synthetic indicators
Contribution and implementation of clustering methods:
The use of cluster analysis to create spatial and non-spatial patterns
Usefulness of econometric models:
Empirical estimation of the relationships between variables through linear and non-linear regression in order to test theoretical approaches, formulate alternative policy proposals and make forecasts and strategic perspectives.
Regression implementation with the use of specialized software:
Model specification, evaluation and analysis of regression results.
Presentation of students’ works
The course evaluation process includes:
An individual work where the student has to propose the methodology and methods of analysis of the phenomenon, he / she wants to examine (50%)
Oral presentation of the individual work with Power Point (20%)
Written examination at the end of the semester (30%)
The above assessment process gives to the students the opportunity to deal with the course during the semester and thus to be in time prepared for the oral presentation of their work as well as for the written examination at the end of the semester.
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