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Module 1: Foundations of Research and Thesis Development
Upon completion of this module, residents will be able to:
• Understand the thesis requirements and academic standards in basic and paraclinical sciences.
• Identify feasible research topics aligned with departmental resources and expertise.
• Formulate clear, testable research questions using established frameworks.
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Module 2: Advanced Literature Review and Research Proposal Writing
This module builds the conceptual, regulatory, and methodological foundation required to design a sound postgraduate thesis- from understanding institutional requirements to translating ideas into structured research questions, hypotheses, and objectives.
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Module 3: Study Design, Methodology, and Data Management
This module builds the conceptual, regulatory, and methodological foundation required to design a sound postgraduate thesis- from understanding institutional requirements to translating ideas into structured research questions, hypotheses, and objectives.
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Module 4: Comprehensive Biostatistics for Thesis Research
To equip learners with the statistical thinking, analytical skills, and practical tools required to analyze thesis data correctly, interpret results responsibly, and present findings in a defensible, publication-ready format.
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Research Methodology and Biostatistics for Postgraduate Residents in Basic Sciences and Paraclinical Sciences
Learning Objectives:
By the end of this lesson, students will be able to:
- Compare cross-sectional, case–control, and cohort study designs in terms of applications and limitations
- Define exposure, outcome, and confounding in observational research
- Calculate and interpret odds ratios and relative risk
- Distinguish between statistical association and causation in observational findings
- Choose an appropriate observational design when experimental design is not feasible
Content:
- Cross-sectional studies: Applications and limitations
- Case–control studies: Case definition; Control selection; Recall and selection bias
- Cohort studies: Prospective vs. retrospective
- Matching strategies and confounding control
- Measures of association: Odds ratio, and Relative risk
- Interpreting association vs. causation
- Choosing observational designs when experiments are not feasible