presentation on final project of the course

this is an exploratory analisys on the dataset provided by the course of data cience and R

This report analyzes the U.S. National Oceanic and Atmospheric Administration (NOAA) storm database to identify which types of weather events are most harmful to population health and which have the greatest economic consequences. The dataset covers events from 1950 to 2011 and includes fatalities, injuries, and property and crop damages. Data were loaded directly from the raw CSV file without external preprocessing. Events were aggregated by type, and damages were standardized into U.S. dollars. Health impacts were measured as the sum of fatalities and injuries, while economic impacts were calculated as the sum of property and crop damage. The analysis highlights that tornadoes are the leading cause of human casualties, while floods and hurricanes are the most costly events. Additionally, correlations between health impacts and economic damages were examined, with extreme outliers removed. The correlation between casualties and economic losses was found to be weak and not statistically significant. These findings suggest that different types of weather events drive human losses and economic damages.