Choosing a discrete distribution Initially modelled as a normal distribution, I'm now trying to capture the probability that human judgments take on a scale of -100 to 100 (arbitrary discrete judgements) using some kind of discrete distribution that's bounded. The distribution has to be centred around a specified mean and SD, but I'm not sure what kind of distribution I could use. Categorical? Multinomial?
I'm not well versed in statistics so any help would be much appreciated.

If you have a ruler and read from it that something measures 8cm and 2mm, you don't assume that the measurement is exact. You assume it's approximate, with some measurement error. The same with measuring things in social sciences. When using the Likert scale, we don't assume that people can have only 5, 7, 201, etc possible states that are measured, but we use it to approximately measure the underlying phenomenon. So in most cases, you don't need a discrete distribution for such cases, the same as we don't use discrete distributions for things like size, weight, time, etc while neither of them is measured with infinite permission. Discrete distributions are needed for inherently discrete things, like counts.
