Biostats in the Medical Literature

Biostats in the Medical Literature

Become more confident when discussing clinical results with leading healthcare providers. This course covers key biostatistical concepts required to review and interpret findings published in the medical literature. Selected scientific publications are reviewed, discussed and criticised in terms of bias, uncertainty and scope.



  • Introduction to statistics: Population vs. sample, variability, role of statistics in scientific research
  • Notion of variables: outcomes, factors, covariates, confounders, etc.
  • Key elements in descriptive statistics: Mean, median, standard deviation, standard error, etc.
  • Principle of statistical inference: notion of risk, significance level, p-value, power of a study, confidence intervals
  • Use of statistical inference in equivalence, non-inferiority and superiority studies
  • Common statistical issues in medical research: sample size calculation, dealing with multiple testing
  • Overview of commonly used techniques in medical research: this part is customised according to the course length and the methods used in the selected papers. It focuses on the principle of each method, data it can handle, results it provides, its scope and limitations
  • Overview of meta-analysis
This course is targeted toward healthcare professionals, medical liaisons, clinicians, and more generally people who need to understand clinical information published in the medical literature. No formal knowledge of biostatistical tools is required to attend the class. The technical level is adapted to the degree of knowledge of participants. Attendees are asked to read the selected papers before the class.
Upon completion of this module, participants will know:
    • The jargon used in biostatistics
    • The statistical principles of scientific research
    • What drives the choice of a statistical method
    • How to criticise scientific papers and to assess the quality of the results and the scope of the conclusions

Recommended Duration: 1 day(s)

Course Materials:


Case Studies:


This Session Has 5 Reviews

  1. D. Traub, MD

    We have selected “Understanding Biostatistics in Medical Literature” for a refresher course with our Medical Marketing team. The intense 2-day program was well received by the entire group; we were particularly pleased about the customization of the contents according to their relevance for our area, and the integration of specifically selected papers and examples throughout the course. Our Creascience trainer has expended significant efforts to ensure that our areas of interest would be optimally covered, which made for a particularly effective learning experience.

  2. Wissam Chahrour, Medical Director

    I highly recommend Natalie for her expertise in biostatistics. Our team of MSLs benefited from her knowledge and explanation.
    Thanks Natalie for a great overview and presentations to our team.

  3. Jean-Bruno Langdeau, Medical Science Liaison, Takeda Pharmaceuticals

    A recent training on the fundamentals of biostatistics with Natalie (to our medical team)_allowed to not only demystify difficult notions of biostats but also addressed in a very customized fashion the unique needs we had expressed. It was efficient and valuable. She is a good teacher, good communicator, and her materials is particularly well built and structured. I highly recommend.

  4. Zakhar Lysov, Medical Science Liaison at Takeda Canada Inc.

    Natalie is a fantastic teacher and a very knowledgeable biostatistician. It was a pleasure learning from her and her ability to customize lessons to make it relevant with our own examples was very valuable and appreciated!

    Thank you so much Natalie!

  5. Debbie Lim, Medical Advisor - Rare Genetics and Hematology, Takeda

    I attended one of Natalie’s biostatistics workshop series and it proved to be very helpful. She is very good at explaining the complexity of biostatistics in a structured and simplified way that made sense and that allowed us to follow. I would strongly recommend Natalie as a biostatistician or teacher for this subject as she is very skilled and has a deep understanding of statistics.

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