  Campaign analysis is an integral part of American democracy and has many
complexities in its dynamics. Experts have long sought to understand these
dynamics and evaluate campaign performance using a variety of techniques. We
explore campaign financing and standing in the polls as two components of
campaign performance in the context of the 2020 Democratic primaries. We show
where these measures exhibit represent similar dynamics and where they differ.
We focus on identifying change points in the trend for all candidates using
joinpoint regression models. We find how these change points identify major
events such as failure or success in a debate. Joinpoint regression reveals who
the voters support when they stop supporting a specific candidate. This study
demonstrates the value of joinpoint regression in political campaign analysis
and it represents a crossover of this technique into the political domain
building a foundation for continued exploration and use of this method.
