Population density is an extremely important factor when considering the likelihood and extent of fatalities as a result of tornado events in a given region. This project considers possible predictors of societal impact for tornado events using population data from the 2010 Census. Using two of the Storm Prediction Center's most well-known and widely-used products, convective outlooks and watches (from 2006 to 2010), as well as the aforementioned population data, the area and population within the outlook and watch areas was computed. This data was then used to analyze relationships between various population measures (total population, percent of population above various threshold values, etc.) and the associated tornado fatalities that occurred within each specified region. Based on this analysis, it was determined that the most significant predictors of fatalities based on convective outlooks are the total area of the outlook (risk area) and the area with greater than or equal to 50 people per square kilometer. The most significant predictor of fatalities based on watches is the total area of the watch region. An analysis comparing Watch Hazard Probabilities to tornado fatalities was also performed. These Watch Hazard Probabilities include the probability of 2 or more tornadoes occurring within the watch area for the valid time, as well as the probability of 1 or more strong (EF2-EF5) tornadoes occurring within the watch area during the valid time. The analysis showed that the strong tornado (EF2-EF5) probability is a very significant predictor of fatalities. In addition to these analyses, a study of tornado fatalities by region, time of day, EF rating, and other factors was undertaken to validate others' findings and to create a complete picture of all the dynamics affecting fatality counts and distribution. This project was undertaken in the hopes that if a significant predictor of tornado fatalities were found, emergency managers, residents, and other end-users of SPC products could use this information to better prepare before a severe weather event. In addition, the factors contributing to higher fatality rates could potentially be addressed in order to save lives in the future.