Currently Empty: ৳ 0.00
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.
0/8
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.
0/9
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.
0/11
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.
0/7
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:
- Classify research variables as categorical, ordinal, or continuous and select appropriate summary statistics
- Calculate and interpret measures of central tendency and dispersion
- Assess whether a dataset follows a normal distribution using appropriate methods
- Distinguish between standard error and standard deviation in research reporting
- Construct and interpret confidence intervals correctly
Content:
- Role of biostatistics in scientific inference
- Types of variables: Categorical (nominal, binary), Ordinal, Continuous
- Scales of measurement and implications for analysis
- Measures of central tendency: Mean, Median, Mode
- Measures of dispersion: Range, Standard deviation, Interquartile range
- Normal distribution: Properties, Assessing normality
- Data transformation and when it is justified
- Standard error vs standard deviation
- Confidence intervals: Meaning and interpretation
- Why “mean ± SD” is often misused