Probability Laws Course
Gain expertise in Poisson processes, exponential waiting times, CLT, and other count models using actual ER arrival data. Master diagnostics, simulation, and straightforward reporting to create dependable, clear probability models for professional statistics in Uganda settings. This course equips you with essential tools for real-world analysis, covering over 50 key concepts in probability modelling.

flexible workload from 4 to 360h
valid certificate in your country
What will I learn?
This course provides hands-on methods to model arrivals and waiting times, focusing on emergency room data. You will explore Poisson and other count models, exponential and advanced waiting-time distributions, applications of the Law of Large Numbers and Central Limit Theorem, simulation techniques, bootstrapping, and diagnostic tools. Develop skills to create open, repeatable analyses, evaluate assumptions, compare models, and communicate uncertainty effectively for practical decision-making in Uganda healthcare contexts.
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 workload.What our students say
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