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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:
- Apply parametric tests (t-tests, one-way ANOVA, Pearson correlation, linear regression) in appropriate contexts
- Apply non-parametric tests (Mann–Whitney U, Wilcoxon, Kruskal–Wallis, Chi-square) when parametric assumptions are not met
- Select the correct statistical test for a given thesis dataset
- Apply appropriate multiple comparison correction methods
- Interpret statistical output from standard software correctly
Content:
- Parametric tests: One-sample, independent, and paired t-tests; ANOVA (one-way); Pearson correlation; Simple linear regression
- Non-parametric tests: Mann–Whitney U; Wilcoxon signed-rank; Kruskal–Wallis; Chi-square and Fisher’s exact test
- Choosing the right statistical test for thesis data.
- Multiple comparisons and correction methods
- When non-parametric tests are preferable
- Interpreting statistical output correctly