On this weeks session, we looked at spatial homogeneity, considering Uniform random vs poisson random. A point pattern is uniformly random if each region gets its fair share of points. Looking at poisson randomness,  we consider the following conditions: Homogeneity, that the number of points in different locations are independent, no two points can be in the same place.

Can we reject a null hypothesis, yes if it can be said that the data was not uniformly random. We looked at the graph of the geographical points in our data and saw from the graphs that the data was not uniformly random.

Questions

* How often do certain protests turn out to be violent

* What kind of demonstrations are more common and in what areas

* what percentage of the protests in each region become violent(are they always protesting?, what goes wrong?)

* Can we classify a future event as violent or not violent by using data from past events within a measurable space and time?