Course Details
Course Information Package
Course Unit Title | RESEARCH METHODOLOGY II | ||||||||||
Course Unit Code | AFRM202 | ||||||||||
Course Unit Details | |||||||||||
Number of ECTS credits allocated | 5 | ||||||||||
Learning Outcomes of the course unit | By the end of the course, the students should be able to:
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Mode of Delivery | Face-to-face | ||||||||||
Prerequisites | AFRM201 | Co-requisites | NONE | ||||||||
Recommended optional program components | NONE | ||||||||||
Course Contents |
1. Introduction: Research process: Steps we follow to do research. 2. Structure of a research report. Writing using appropriate layout, style,organization, structure and referencing a research project to academicstandards. Synthesize information in a focused way in order to develop andsupport arguments through a project in which students will apply themethodological concepts obtained in lectures 3. Understanding different methodological approaches. Main researchstrategies and elements of a research design. An introduction to various methodused for research. Structure of a questionnaire. 4. Quantitative research: Analysis and organization of data. Analysis oftwo variables and the relationship between them. Examples using real data inlab, along with using appropriate software packages such as SPSS, Excel, Stataand other. 5. Statistical methods: Regression analysis (least squares method) forquantitative data. Introduction to Simple Regression (between two variables).Analysis and explanation of the results. 6. Multiple regressions: analysis between more than two variables,interpretation of the results. 7. Extensions of multiple regressions using dummy variables, logarithms andquadratics. Hypothesis testing using basic statistical tools on thesignificance of the results. 8. Application of all the above regression analysis tools using actual dataand the appropriate software in a project. 9. Orally present part of the research project | ||||||||||
Recommended and/or required reading: | |||||||||||
Textbooks |
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References |
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Planned learning activities and teaching methods | Lectures, discussions, examples, application using real data in lab. The students should be able to collect appropriate data and use descriptive and regression analysis methods, along with appropriate software, in order to answer a research question in mind. They should be able to interpret their results following the purpose of any quantitative project. Use of software packages for data processing Collecting and analyzing data using quantitative methods (descriptive statistics and regression analysis) Oral presentations, feedback based on the evaluation of the research project submitted | ||||||||||
Assessment methods and criteria |
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Language of instruction | English | ||||||||||
Work placement(s) | NO |