rootX said:Central Limit theorem looks appropriate using Gaussian distribution.
A random process is a mathematical model used to describe the behavior of a system over time, where the outcome of the process is determined by chance or probability. It involves a sequence of random events that occur over time.
A Poisson process is a type of random process where events occur randomly and independently of each other over a continuous time interval. It is often used to model the arrival of customers or requests in a queue, radioactive decay, or the occurrence of natural disasters.
A process can be considered a Poisson process if it satisfies the following criteria:
The probability of completing n jobs in t hours can be calculated using the Poisson distribution formula, which takes into account the average rate of job completion (lambda) and the desired number of jobs to complete (n). The formula is: P(n,t) = (lambda*t)^n * e^(-lambda*t) / n!
Yes, the Poisson distribution is commonly used to model real-life situations in various fields such as physics, biology, finance, and engineering. It is especially useful in situations where the events occur randomly and independently over time, making it a good approximation for the behavior of the system.