Probability Laws Course
Gain mastery in Poisson processes, exponential waiting times, CLT, and other count models with real ER data. Develop skills in diagnostics, simulation, and clear reporting to create dependable, transparent probability models for professional use in statistics and operations.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This course equips you with hands-on methods to model arrivals and waiting times, emphasising ER datasets. You will explore Poisson and other count models, exponential and advanced waiting-time distributions, applications of LLN and CLT, simulation techniques, bootstrapping, and diagnostic tools. Learn to develop clear, reproducible analyses, evaluate assumptions, compare models effectively, and communicate uncertainty for informed real-world decisions.
Elevify advantages
Develop skills
- Poisson & count modelling: build, diagnose, and refine ER arrival models quickly.
- Waiting-time modelling: fit exponential and other distributions to real ER delay data.
- CLT & LLN for operations: measure ER averages, risks, and tail probabilities.
- Simulation & bootstrap: perform fast Monte Carlo checks and small-sample intervals.
- Model validation & reporting: check assumptions and produce clear, reliable 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 workloadWhat our students say
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