I am not sure how to use that...Orodruin said:Hint: 100 is a fairly large number.
http://thomaswhitham.pbworks.com/f/6.Po+to+norm.pdfSilviu said:I am not sure how to use that...
The Poisson distribution is a probability distribution that is used to model the number of events that occur in a fixed interval of time or space. It is often used to analyze rare events or situations where events occur independently of each other.
The Poisson distribution assumes that the events occur at a constant rate, events occur independently of each other, and the probability of an event occurring in a given interval is proportional to the length of the interval.
The Poisson distribution is different from other distributions, such as the normal distribution, because it is a discrete distribution, meaning that the possible outcomes are countable and not continuous. It also only has one parameter, the rate parameter, whereas other distributions may have multiple parameters.
The Poisson distribution is commonly used in areas such as insurance, finance, and healthcare to model the number of rare events, such as accidents, defaults, or medical emergencies. It is also used in quality control to monitor defects in a production process.
The Poisson distribution can be used to analyze data from studies that involve counting the number of occurrences of a certain event, such as the number of bacteria in a sample or the number of mutations in a gene. It can also be used to test the significance of observed frequencies in comparison to expected frequencies.