Course description

This course introduces learners to the most widely used statistical software and programming tools in medical informatics and research, including R, SPSS, Stata, and Python. Whether you are a healthcare professional, student, or researcher, this course equips you with practical data analysis and programming skills essential for evidence-based practice and scientific discovery.

Participants will explore the fundamentals of data management, visualization, and statistical modeling across different platforms, while gaining insights into choosing the right tool for specific tasks in clinical research, epidemiology, and health informatics. Through real-world datasets, case studies, and guided projects, learners will build confidence in applying statistical software for research, reporting, and decision-making in healthcare.

By the end of this course, you will be able to design, analyze, and interpret research studies using multiple software environments, preparing you for advanced work in public health, medical informatics, data science, and clinical trials research.

What will i learn?

• Understand the role of statistical software in medical informatics and clinical research.
• Import, clean, and manage healthcare datasets in R, SPSS, Stata, and Python.
• Perform descriptive, inferential, and regression analyses across platforms.
• Visualize health and clinical research data for publications and reports.
• Select the most appropriate software tool for different research contexts.
• Apply programming skills to real-world health research and clinical trials.
• Interpret statistical results in line with evidence-based practice.

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