Week 10: Poisson Distribution
In statistics, a Poisson distribution is a statistical distribution that shows how many times an event is likely to occur within a specified period of time. It is used for independent events that occur at a constant rate within a given interval of time.
The Poisson distribution is a discrete function, meaning that the event can only be measured as occurring or not as occurring, meaning the variable can only be measured in whole numbers. Fractional occurrences of the event are not a part of the model. it was named after French mathematician Siméon Denis Poisson.
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Course Material
- Week 1: Introduction Statistics
- Week 2-3: Introduction to set theory and probability
- Week 4: Types of Probability
- Week 5: Independent events and Laws of Probability.
- Week 6: Random variables and Probability Distributions
- Week 7: Discrete Probability Distributions (Binomial distribution)
- Week 8: Bayes' Theorem
- Week 9: Mid Term Exam
- Week 10: Poisson Distribution
- Week 11: Geometric and Negative Binomial Distributions
- Week 12-13: Linear Regression, curve fitting and correlation
- Week 14: Continuous probability distributions (Exponential)
- Week 15-16: Normal Distribution
- Week 17: Hyper-geometric Distribution
- Week 18: Final Term Exam
- Chapters 15
- Department Electrical Engineering
- Teacher
Habiba Mustafa
