  The following is a write up of the progress of modeling data from the K12
organization \cite{Riedman_2023}. Data was characterized and investigated for
statistically significant factors. The incident data was spilt into three sets:
the entire set of incidents, incidents from 1966 - 2017, and incidents from
2018 - 2023. This was done in an attempt to discern key factors for the
acceleration of incidents over the last several years. The data set was cleaned
and processed primarily through RStudio. The individual factors were studied
and subjected to statistical analysis where appropriate. As it turns out, there
are differences between media portrayals of shooters and actual shooters. Then,
multiple regression techniques were performed then followed by ANOVA of the
models to determine statistically significant independent variables and their
influence on casualties. Thus far, linear regression and negative binomial
regression have been attempted. Further refining of the methods will be
necessary for Poisson regression and logistic regression to be viably
attempted. At this point in time a common theme among each of the models is the
presence of targeted attacks affecting casualties. Further study can lead to
improved safe guarding strategies to eliminate or minimize casualties. Further,
increased understanding of shooter demographics can also lead to outreach and
prevention programs.
