This is a guide for a friend and colleague who is planning to get a new Samsung phone and tablet.

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.

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Intro to Biostatistics (BIOL 327) September 17, 2025 Fall 2025 William & Mary

ggplot(data = diamonds, mapping = aes(x= price,y= carat , color = cut ))+ geom_point()+ theme_light()+ facet_wrap(~cut)+ xlab("Diamonds Price")+ ylab("Diamond Carat") + ggtitle("Scatterplot")