Data Analytics
Statistical Analysis
Hurricane Maria | Puerto Rico
In 2017, Hurricane Maria wrought catastrophic devastation to Puerto Rico. Maximum sustained winds reaching 155mph, coupled with heavy rain and storm surge destroyed homes, businesses, and infrastructure systems, leaving millions without access to power, water, or food supplies. With disasters this size, comes the challenge of accounting for and accurately quantifying all damage in a timely manner. In some cases, it’s not possible – the damage is too widespread, and tax-payer-funded rebuilding efforts limit the time needed to assess all disaster-related damage. Nevertheless, our mission to restore devastated regions to their original condition remains. In an effort to satisfy both demands, our team employed statistical sampling and modeling of damaged sites to more efficiently develop cost estimates. I drew on data from site inspections and extrapolated the cost to rebuild sites with similar location and function. The methodology saves time and effort – ensuring that projects are obligated sooner while reducing overall federal spending.