Probability Laws Course
Master Poisson processes, exponential waiting times, the Central Limit Theorem, and alternative count models using real emergency room arrival data. Acquire skills in diagnostics, simulation, and clear reporting to develop reliable, transparent probability models for professional statistical applications.

4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This course equips you with practical tools to model arrivals and waiting times, emphasising emergency room data. Explore Poisson and alternative count models, exponential and advanced waiting-time distributions, applications of the Law of Large Numbers and Central Limit Theorem, simulation techniques, bootstrapping, and diagnostic methods. Develop transparent, reproducible analyses, evaluate assumptions, compare models, and communicate uncertainty effectively to inform real-world decisions.
Elevify advantages
Develop skills
- Poisson and count modelling: construct, diagnose, and refine ER arrival models swiftly.
- Waiting-time modelling: fit exponential distributions and alternatives to actual ER delay data.
- CLT and LLN for operations: quantify ER averages, risks, and tail probabilities.
- Simulation and bootstrapping: perform rapid Monte Carlo checks and small-sample intervals.
- Model validation and reporting: test assumptions and produce clear, defensible results.
Suggested summary
Before starting, you can change the chapters and the 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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