Academics 

I completed this project about COVID-19 database. I designed the Relational Database Model (RDM), imported tables in MS Access, wrote SQL queries, structured the data hierarchically, and generated reports. The project examined the complex relationships between patients, hospitals, states, virus variants, and vaccinations, exploring one-to-many and many-to-many relationships. The goal was to analyze infection and mortality rates across different states and hospitals, identify the most affected patient types, and evaluate vaccine effectiveness and other demographic trends. 

At the Anti-Defamation League (ADL), my role focused on various aspects of marketing and outreach. I learned to effectively communicate and present ideas to a wide audience. This is one of the one-pagers that I create which clearly communicates ADL's mission and how individuals can contribute. This deepened my understanding of brand and marketing strategies and equipped me with the skills necessary for promoting and increasing the visibility of programs and initiatives.

The project involves analyzing the relationship between independent (IV) and dependent variables (DV), focusing on addressing missing data and constructing a statistical model. The first part uses R programming to impute missing data, create scatter plots, and conduct analysis of variance (ANOVA) to assess the relationship between IV and DV. The second part further refines the model using data transformations, binning, and a lack of fit (LOF) test to improve accuracy in predicting the DV based on the IV.

The project focuses on identifying the model that explains the relationship between a dependent variable (Y) and environmental (E1-E4) and genetic (G1-G20) variables. Using statistical techniques such as stepwise regression, subset selection, and a Box-Cox transformation to improve model fit, the analysis identifies significant correlations, particularly between Y and the environmental variables E1, E3, E4, and the gene-gene interaction between G11 and G13. The final model, with an adjusted R-squared of 0.5978, highlights the influence of both environmental and genetic factors on the outcome variable​.