Welcome to the R for Medical Statistics course, designed for final year undergraduates/master’s students seeking a career in data within the pharmaceutical industry. This comprehensive 2-month online course will empower participants with essential skills in R programming tailored for a career in medical statistics. Join us on a transformative journey into the world of R for medical statistics. Enroll today to enhance your skills and make your CV stand out in the competitive pharmaceutical industry!

Course Goals:

  • Create R programmes and analyze data in a reproducible way
  • Harness the power of open-source tools for statistical approaches
  • Learn techniques for data visualization and interpretation
  • Network with like-minded individuals globally

Course Structure:

  • Duration: 2 months
  • Time Commitment: Approximately 2 hours per week
  • Format: Online
  • Pre-recorded tutorials with slides
  • Live Q&A sessions
  • Virtual networking events

Target Audience:

  • Final year undergraduates aspiring to work with data in the pharmaceutical industry
  • Master's students with a keen interest in medical statistics

A basic understanding of statistics and modeling.

Key Topics Covered:

  • Introduction to RStudio
  • R Basics
  • Mathematics in R
  • Reading in Data
  • Working with Data Frames
  • Working with Distributions
  • Graphics
  • Linear Regression and ANOVA
  • Modelling
  • The Pharmaverse package

Interactive Elements:

  • Virtual Networking
  • Live Q&A Sessions
  • Live Tutorials

Course Materials:

  • Recorded tutorials with slides
  • Mini-projects simulating real-world pharmaceutical industry scenarios
  • Access to local groups within universities

Students: 199 Euros 


Your instructor

Dr. Alexander Schacht is an accomplished statistician with an extensive background in biostatistics, evidenced by a PhD from the University of Göttingen and over 20 years of experience in the healthcare sector. Specializing in advanced phases of clinical research, Alexander has been pivotal in phase IIIb and IV studies, balancing the intricacies of regulatory compliance with commercialization and HTA submissions. His profound understanding of non-parametric statistics has not only led to the authorship of over 70 scientific papers but has also established him as a prominent voice at international conferences, where he shares insights on topics ranging from methodological innovations to data-driven decision-making in the pharmaceutical industry.

Alexander's passion for teaching is rooted in his commitment to equipping the next generation of medical professionals with robust statistical know-how. As the founder of The Effective Statistician, he has developed a platform that transcends traditional learning, incorporating a popular weekly podcast and a suite of online resources to foster a dynamic educational community. His engagement with students extends beyond the course content, drawing on a wealth of real-world experience and a fervent belief in the power of statistics to positively impact patient outcomes worldwide. Alexander's proactive approach to teaching, coupled with his active roles in professional societies focused on benefit-risk assessment and data visualization, make him uniquely qualified to lead medical professionals through the data-driven landscape of modern medicine.

Chantelle Cornett, BSc (Hons), MSc, is a Health Informatics PhD Candidate at the University of Manchester and a Statistician at The Effective Statistician. With over three years of experience, she excels in data analytics, statistics, and statistical programming. Her academic foundation includes a BSc in Statistics from University College London and an MSc in Medical Statistics from the London School of Hygiene and Tropical Medicine.

Chantelle's work is marked by a publication in the "Research Synthesis Methods" journal highlighting her contributions to statistical methodologies in health informatics. She is committed to leveraging data to enhance healthcare outcomes, reflecting her passion for both the academic and practical applications of her field.

Her dedication extends beyond professional achievements; she has volunteered as a data analyst at The Neurological Alliance, applying her expertise to support individuals with neurological conditions. This role underscores her commitment to using statistics for societal benefit.

Aiming to drive innovation in statistical modelling, Chantelle's career aspirations focus on the development of new statistical methods to tackle complex health informatics challenges notably those in women's health. Her work embodies a blend of rigorous academic research and practical application, aimed at advancing the field of health informatics and statistics.