# What is overdispersion and what is its impact on the indices?

TRIM assumes the count data to be Poisson distributed. Overdispersion indicates the degree of deviation of Poisson distribution, and influences the standard errors of the indices and other parameters, not the indices itself. A high overdispersion may result from a lack-of-fit of the model which implies that better models might reduce overdispersion. But a high overdispersion could be a characteristic of the species studied, such as moving in flocks.