Probability Laws Course
Master Poisson processes, exponential waits, CLT, and alternative count models using real ER arrival data. Learn diagnostics, simulation, and clear reporting to build reliable, transparent probability models for professional statistical work.

from 4 to 360h flexible workload
certificate valid in your country
What will I learn?
The Probability Laws Course gives you practical tools to model arrivals and waiting times, with a focus on ER data. Learn Poisson and alternative count models, exponential and richer waiting-time distributions, LLN and CLT applications, simulation, bootstrapping, and diagnostic checks. Build transparent, reproducible analyses, assess assumptions, compare models, and report uncertainty clearly for real-world decisions.
Elevify advantages
Develop skills
- Poisson & count modeling: build, diagnose, and refine ER arrival models fast.
- Waiting-time modeling: fit exponential and alternatives to real ER delay data.
- CLT & LLN for operations: quantify ER averages, risks, and tail probabilities.
- Simulation & bootstrap: run quick Monte Carlo checks and small-sample intervals.
- Model validation & reporting: test assumptions and write clear, defensible results.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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