Underdispersion is when there is less variability than there 'ought' to be in the data. Eg, the variance of counts could be less than the mean, whereas the variance of a Poisson should equal the mean.
Underdispersion is when there is less variability than there 'ought' to be in the data. For example, the variance of a set of counts could be less than the mean, whereas the variance of a Poisson should equal the mean. Underdispersion can be contrasted with overdispersion, which is a much more common phenomenon.
