micromass said:Simple do 18.17.16.15.14.13.12.11.10.9.8.7.6.5.4.3.2
micromass said:What does 18! mean?
I have tried that several times but keep coming up with the wrong answer.Char. Limit said:Well, there is usually a factorial button in your calculator, somewhere.
Try under the MATH menu.
Yep, I see the factorial button.Char. Limit said:Well, there is usually a factorial button in your calculator, somewhere.
Try under the MATH menu.
Yes I'm sure.Char. Limit said:Well, your formula should be correct. Are you sure your x and [itex]\lambda[/itex] values are correct?
A Poisson distribution is a probability distribution that models the number of events occurring within a specific time or space when the events are independent and the average rate of occurrence is known. It is commonly used in science to analyze and predict rare events, such as the number of mutations in DNA or the number of radioactive particles emitted from a substance.
The mean and variance of a Poisson distribution can be calculated using the formula: mean = rate parameter and variance = mean. For example, if the average rate of occurrence is 5, then the mean and variance would both be 5.
No, a Poisson distribution is only suitable for discrete data, meaning that the data can only take on whole number values.
To determine if a dataset follows a Poisson distribution, you can plot the data on a histogram and see if it resembles the typical shape of a Poisson distribution, which is a skewed right, bell-shaped curve. You can also use statistical tests, such as the chi-square test, to assess the goodness of fit to a Poisson distribution.
A Poisson distribution assumes that the events are independent and occur at a constant rate, which may not always be the case in real-world situations. It also only works for discrete data and may not be suitable for datasets with large values or a wide range of values. Additionally, the accuracy of predictions using a Poisson distribution decreases as the mean increases.