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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:
- Justify the scientific and ethical importance of adequate sample size in research
- Define and apply the core determinants of sample size: effect size, alpha error, statistical power, and variability
- Calculate sample sizes for experimental and observational studies using appropriate formulas and software
- Recognise and correct common sample size justification errors in thesis protocols
Content:
- Why sample size matters scientifically and ethically
- Core determinants: Effect size; Alpha error; Power; Variability
- Sample size approaches for: Experimental studies and Observational studies
- Software tools for sample size calculation
- Handling feasibility constraints honestly
- Common sample size justification mistakes