This paper is a personal exploration of where the ideas of "distribution" that we are trying to develop in students come from and are leading to, how they fit together, and where they are important and why. We need to have such considerations in the back of our minds when designing learning experiences. The notion of "distribution" as a lens through which statisticians look at the variation in data is developed. I explore the sources of variation in data, empirical versus theoretical distributions, the nature of statistical models, sampling distributions, the conditional nature of distributions used for modelling, and the underpinnings of inference. (Contains 7 figures.)