John Hopkins Coursera Capstone Project Presentation

This report is for the John Hopkin's Coursera Data Science Capstone project. It summarises textual features of three files containing blog text, news text, and twitter text, in preparation to develop a product for word prediction.

The purpose of this report is to identify the types of storm events that are most harmful to the population health within the United States and to identify the types of storm events that cause the greatest economic cost using the National Oceanic and Atmospheric Administration (NOAA) storm dataset. [National Weather Service Instruction 10-165] (https://d396qusza40orc.cloudfront.net/repdata%2Fpeer2_doc%2Fpd01016005curr.pdf) is available for reference. The dataset contains 60 years of storm events recorded between 1951 and 2011. Free-text input of data, directive changes, and the merging of data from individual counties and states has created many inconsistencies, especially in the categorization of storm event types `EVTYPE`. Storm events recorded in the last twenty years account for approximately 80% of the data and is considered to be a more reliable source for analysis. Storm event data was analyzed for the time period between November 1991 and November 2011. It was found that **excessive heat** and **tornados** are the most dangerous to health, causing thousands of fatalities and injuries. **Flood** has the greatest economic damage to crops, while **ice storm** has the greatest economic impact on property.