We raised a $20m Series A led by Coatue + Accel! Click here to read the announcement.

Google Sheets

The POISSON function in Google Sheets is used to calculate the probability of an event occurring. The function takes two arguments: the number of events that have occurred, and the average number of events that would occur in the absence of any bias. The function then calculates the probability of the event occurring at least once in the given number of trials.

The syntax of the POISSON function in Google Sheets is as follows:

=POISSON(x, mean, false_mean)

Where "x" is the number of occurrences, "mean" is the expected number of occurrences, and "false_mean" is the expected number of occurrences when the Poisson distribution is false.

The Poisson distribution is a discrete probability distribution that arises in many situations in which the number of events, or successes, in a given time interval is relatively small and there is no obvious pattern to the occurrences. It is commonly used to model the number of telephone calls received by a call center per hour, the number of defective items produced by a machine per hour, or the number of bacteria in a culture at any given time.

One way to use the Poisson distribution in Google Sheets is to calculate the probability of a certain number of events occurring in a given time interval. For example, you could use it to calculate the probability of receiving six phone calls in an hour. You can also use it to calculate the expected number of events in a given time interval. For example, you might want to know the average number of phone calls that a call center can expect to receive in an hour.

There are several occasions when you should not use POISSON in Google Sheets. One is when you have a binomial distribution rather than a Poisson distribution. Another is when the number of events is less than 10. Additionally, you should not use POISSON when the mean is greater than the variance.

In Google Sheets, there are a few similar formulae to POISSON. One is GEOGEBRAS, which calculates the GEE estimator for a Poisson regression model. Another is GENPOIS, which calculates the Generalized Poisson Distribution. There is also a TRIGGERPOISSON function, which calculates the trigger points for a Poisson process. Finally, there is the POISSON function itself, which calculates the probability of a Poisson event.

Get started with Causal today.

Build models effortlessly, connect them directly to your data, and share them with interactive dashboards and beautiful visuals.

Build models effortlessly, connect them directly to your data, and share them with interactive dashboards and beautiful visuals.