West Chester University, BS in Mathematics, Statistics Concentration

      Graduated: 5/2024

Endo Pharmaceuticals, Biostatistics Internship  May–August, 2022 | June 2023-August 2024

• Gained knowledge on drug development and hands-on experiences on clinical study, ie., be familiar with Protocol/SAP/CSR, CDISC standards on SAS datasets and generation of TLF outputs for CSR.
• Explored the use of the statistical software R in conjunction with various R packages to summarize and visualize data, especially on data monitoring dynamically. The R packages include SafetyGraphics, SafetyCharts, and safetyExploreR, etc.
• Examined the functionality of R in the creation of CSR Outputs (TLFs) based on clinical study data. The R packages includes tplyr, huxtable, sassy, ggplot2, dplyr, etc.
• Usage of SAS and R statistical tests to check functionality across statistical programs with a view of their usage in pharmaceutical research and analysis
• Examined missing data handling and analysis with real world clinical trial data in R - usage of mice and mmrm packages
• Exploration of sdtm.oak package for the creation of SDTM CDISC datasets from raw clinical trial data in R.

Experimental Design

• Design of Experiments, ANOVAs, block, factorial, and split plot designs, and response surface analysis

Statistics Capstone

• Statistical report writing, presentations, statistical consulting, sampling design, and resume writing.

Principles of Experimental Analysis

• ANOVA techniques and model building for data with continuous response variables in SAS. Model creation, regression diagnostics, one- and two-way ANOVA.

Applied Statistics

• Simple and multiple linear regression methods and linear time series analysis with an emphasis on fitting suitable models to data and testing and evaluating models against data.

Basics of Statistical Learning

• Introduction to statistical learning and predictive modeling. Parametric and nonparametric models used for visualizing and understanding complex data sets.

Topics in Advanced Statistics

• Select topics in categorical analysis, nonparametric and time series analysis. Statistical programming and simulations.

Introduction to and Intermediate R

• Data manipulation, data visualization, data analysis: ANOVA, linear models, mixed-effect models, logistic regression, and writing R functions

Introduction to and Intermediate SAS

• Data manipulation, data output, data summary, and data analysis, TTEST, GLM, REG, MANOVA, FACTOR, LOGISTIC, and MIXED procedures

Introduction to Web Design

• Design and construction of simple to complex web sites using HTML, CSS, and JavaScript

Organization of Data

• Basics of data, databases, and database management. Use of SQL Queries to create and manipulate data in a database and the creation of a conceptual database design.

Technical Writing

• - Instruction in the forms and techniques of written, oral, and visual communication currently practiced in the scientific and technical professions.

• Computer Languages: R, SAS, Java, C/C++, MatLab
• Microsoft Office: MS Excel, MS Word, PowerPoint, Visio
• IDEs: RStudio, Eclipse, Visual Studio, SAS IDE
• Database design and implementation: MS SQL
• Script languages: CSS, HTML, Javascript
• Image editing/3D software: Blender, Photoshop