a Coursera Course in Conjunction with John Hopkins and Swiftkey®
The goal of this project is just to display that I've gotten used to working with the data and that I'm on track to create my prediction algorithm.
Taking 272 observations of the duration the eruptions and the length of time between them we were able to build a prediction algorithm that would identify how long the eruption would take place given the amount of time between the last eruption. We were able to conclude that the more time between eruptions, the more water would build up and the longer the geyser would discharge.
This report acts as an aid for municipal managers or other government officials looking to prioritize resources for various weather-related events. Though we make no specific recommendations, we are able to tease out of the NOAA Storm Database, those events that have the largest impact on health and the economy. Utilizing simple graphs, charts and summaries the reader will find that our results clearly show a primary source of concern. This report has been created in such a way that these commands are reproducible containing every programming code used in the analysis along with a description of the thinking that goes into such an analysis. The results will show that the types of events most harmful with respect to health are primarly wind related. Conversely, the events with the greatest economic consequences revolve around the costal areas and are primarly water related.