This dissertation discusses observing causality within point processes. Firstly, a novel hypothesis test for distinguishing between inhomogeneity and causal clustering is described, validated on simulations, and then used in shooting data. Next, the hypothesis test is also applied to temporal disease data to identify social contagion mechanisms. Lastly, a discussion of a novel potential outcomes framework as applied to point process data is defined and applied to simulated data.