Probability Theory in R Programming || Classical Probability || Empirical Probability

Biostatistics is everywhere—in clinical trials, epidemiology, genetics, and public health. But too often, it's taught as abstract theory, detached from the real questions researchers and analysts try to answer.

What if you could learn biostatistics, how it’s meant to be used—in context, with real data, and in a language built for the job?

I'm thrilled to invite you to my new course:
🎓 Practical Biostatistics with R

This isn’t a traditional statistics course. It’s a hands-on exploration of how biostatistics works through real-world datasets, reproducible workflows, and the power of R.

In this course, we’ll tackle questions like
How do you make valid inferences from messy real-world data?
What does statistical significance mean in a clinical context?
How do we balance model complexity with interpretability in public health research?

You’ll not only learn statistical methods—you’ll learn how to think statistically.

You’ll come away with:
Practical fluency in R for data analysis and visualization
The ability to run and interpret key biostatistical tests
A deep understanding of regression, modeling, and reporting
Confidence to work with real-world biomedical and health data

If you're a student, researcher, or professional ready to move beyond theory and into application, this course was built for you.

👉 [https://www.udemy.com/course/practica...]
(Discounts available for early sign-ups.)

Statistics is not just about numbers. It’s about questions, decisions, and lives.
Let’s make your skills matter.

See you inside.