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Research Methodology – Statistics

Statistical Reasoning in Clinical Research: From Hypothesis Testing to Evidence-Based Practice

Course details
Non-credit or Credit course
Non-credit course
Teacher
Prof. Johannes Vester
Category
Biostatistics
Research methods
Dimension
Theoretical Neuroscience
Level
Expert

Statistical reasoning is at the heart of evidence-based medicine. This series of lectures by Prof. Johannes Vester guides participants through the essential concepts that ensure the scientific validity and interpretability of clinical research.

The course begins with the fundamentals of hypothesis testing through intuitive examples such as the coin-flip model, introducing the null hypothesis, P-values, and the common pitfalls in interpreting statistical significance. It then advances to the principles of effect sizes and confidence intervals, explaining why these measures often provide more meaningful insights than p-values alone. Participants will learn how to apply these concepts in both superiority and non-inferiority trials and understand their relevance to modern reporting standards, including CONSORT, ICH, and FDA guidelines.

Building on this foundation, the lectures explore how meta-analyses serve as cornerstones of evidence-based medicine, driving the development of clinical guidelines. Attendees will learn how to read and interpret forest plots, understand the difference between fixed and random effects, and assess the heterogeneity and quality of evidence using the GRADE system.

The final session focuses on the importance of quality assurance in clinical research. Participants will gain insight into modern risk-based approaches and centralised statistical monitoring, examining why clinical trials fail and how robust design and ongoing quality control can prevent common errors. Real-world examples illustrate how these principles translate into successful, high precision randomized controlled trials.

By the end of the course, participants will have a stronger grasp of statistical reasoning, evidence interpretation, and quality assurance, equipping them with the tools to critically evaluate, design, and conduct clinical studies with scientific rigour.

This course is offered in collaboration with the Doctoral School of Neuroscience, “Iuliu Hațieganu” University of Medicine and Pharmacy, Cluj-Napoca.

Course Features
Understand the fundamental principles of hypothesis testing, P-values, and statistical significance.
Learn to interpret and apply effect sizes and confidence intervals in clinical research.
Differentiate between superiority and non-inferiority trial designs and understand regulatory expectations (CONSORT, ICH, FDA).
Gain the ability to critically interpret meta-analyses, including forest plots, heterogeneity, and GRADE assessment.
Recognise the key role of quality assurance and risk-based monitoring in ensuring reliable and high-quality clinical trials.
Develop a critical mindset for evaluating and improving the methodological and statistical quality of biomedical studies.

Lessons

Number of lessons: 2