In this project, we use R text mining tools to build a statistical model for word sequences. The model will predict the next word as a user types - similar to the Swiftkey text messaging app. For example, when the user types: "I went to the " : the predictor should present options for what the next word might be. For example, the three words might be "gym, store, restaurant".

We analyze the U.S. National Oceanic and Atmospheric Administration’s (NOAA) storm database to determine the economic impact of different weather events. The goal of the analysis is to rank the storm events based on (1) public health impact and (2) economic impact. Our hope is that this ranking will inform policy makers as they allocate emergency management funds to the events with the greatest economic impact.