As a data scientist I use statistics to improve decision-making, forecast potential outcomes, and build better understanding of how an organization works. Below are some examples of the statistical I can use to help accomplish those goals.


Sentiment Analysis

A project showcasing my R programming ability. I went through a large dataset of credit report complaints from the Consumer Financial Protection Bureau's dataset on complaints. This shows my ability to organize and analyze through large messy data and find actionable information.


Analysis of Nosocomial Infection Control Efficacy in US Hospitals

The core objective of our project is to assess the variation in nosocomial (hospital-acquired) infection risks across different geographic regions within the United States. We aim to determine whether there are statistically significant differences in infection probabilities among four distinct regions, shedding light on potential regional disparities in healthcare-associated infections.