From Idea to Impact: Your Partner in Clinical Research That Matters
In 2025, the DCR introduced a new course: “Fundamental Statistics for Clinicians.” Recognizing a gap in professional training, the DCR Statistics & Methodology team collaborated with the DCR Education team to create a course that makes both core and advanced statistical concepts approachable and directly applicable to clinical research.
The first cohort brought together 28 participants from a variety of departments, including the Inselspital, for a course taking place on four separate days. Through a hybrid learning model, clinicians first engaged in self-directed online study, building a foundation at their own pace. They then came together in onsite, faculty-guided peer-group sessions, where theory met practice and concepts were reinforced through discussion and real-world examples. By the end of the course, participants had strengthened their confidence and competence in statistics, gaining tools to design, analyze, and interpret clinical research.
Goals
The Fundamental Statistics for Clinicians course prepares clinicians to apply core statistical concepts in the context of clinical research.
Participants will learn to explain key statistical principles, distinguish between common study designs and justify their selection based on specific research objectives, and construct research questions that are amenable to statistical testing. They will develop the ability to outline and critically review the key components of a statistical analysis plan and study protocol. In addition, learners will assess when advanced trial designs - such as adaptive, factorial, or cluster-randomized trials - are warranted and appraise their implications for study implementation, data interpretation, and ethical oversight.
Learning Objectives
By the end of this course, learners will be able to
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Describe and apply core statistical concepts relevant to clinical research, including data types, distributions, and key measures of central tendency and variability.
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Critically evaluate and select appropriate study designs (e.g., observational vs. interventional, randomized vs. non-randomized) based on research objectives and methodological rigor.
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Formulate clear, testable clinical research questions that align with statistical principles and are amenable to quantitative analysis.
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Develop and interpret the key components of a statistical analysis plan, including hypotheses, sample size justification, statistical methods, and outcome measures.
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Assess when advanced trial designs (e.g., adaptive, cluster-randomized, or Bayesian designs) may be required, and describe their implications for trial conduct, data interpretation, and ethical considerations.
“
I found that it gives a very good overview over the basic principles but it doesn't start at zero. [...]
It builds up on [prior knowledge] very well, but it still covered a lot of general ground. It gave me a very good overview, which was very coherent
Lara Brockhus
Research Fellow, BIHAM (Berner Institut für Hausarztmedizin)