Probability Laws Course
Gain mastery over Poisson processes, exponential waiting times, Central Limit Theorem, and alternative count models through real emergency room data analysis. Acquire expertise in diagnostics, simulation, and precise reporting to construct reliable, transparent probability models essential for professional statistical applications in operations.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This course equips you with practical 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 transparent, reproducible analyses, evaluate assumptions, compare models, and communicate uncertainty effectively for informed decision-making.
Elevify advantages
Develop skills
- Poisson and count modelling: construct, assess, and improve ER arrival models efficiently.
- Waiting-time modelling: apply exponential and other distributions to actual ER delay datasets.
- CLT and LLN in operations: measure ER averages, risks, and extreme probabilities accurately.
- Simulation and bootstrapping: perform rapid Monte Carlo validations and confidence intervals for small samples.
- Model checking and reporting: verify assumptions and produce clear, robust findings.
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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