Professional Summary
A skilled presented, with 3 years of experience presenting and creating educational presentations. A very organized and diligent worker, with experience in working on research projects for a nonprofit organization.
Work Experience
Peer Educator - Quantitative Research and Community Engagement LeadAugust 2022 - Present
West Chester University | West Chester, PA
In charge of creating events for the WCU student body to help students meet and engage with other students. Created events from start to finish, including planning guides, room reservations, and creating social media content to promote the events. Addtionally, created and presented educational presentations for WCU student, staff, and faculty.
Sales Intern
May 2024 - Present
CYTO|PHL | Philadelphia, PA
Tasked with creating event contracts to send to clients. Created several forms of marketing materials for newsletters, Instagram, and for in office use. Ran and analyzed sales reports for the company.
Education
West Chester University, August 2024 - May 2026Masters of Science in Applied Statistics
West Chester University, August 2021 - May 2025Bachelors of Science in Mathematics (Accelerated) - Statistics Concentraion
Minor in Digital Marketing
Publications & Research
Partook in an independent study in the Spring 2024 semester with the Jewish Relief Agencey, a nonprofit organization based in Philadelphia. The independent study concluded with a poster submission to the College of Science and Mathematics Poster Day, the poster was approved by the advisor of the independent study, Professor Pyott.
Projects & Portfolio
1. A Project on Bootstrapping and Multiple Linear Regression on Body Mass Index in Diabetic and Non Diabetic Patients.
2. A Project on Logistic Regression In Stroke and Non Stroke Patients.
3. A Project on Dispersed Poisson Regression for Cyclist Count.
4. A Project on Exponential Smoothing of a Time Series with Trend and Seasonality for New Home Sales.
5. STA 321 Logistic Regression Project: Predicting a Patient’s Odds of CHD.
6. Analyzing Different Sampling Methods for Bank Loan Default Data.
Course Work
STA 512- Principles of Experimental AnalysisThis course provides technology-driven introduction to regression and other common statistical multivariable modeling techniques. Emphasis on interdisciplinary actions.
STA 511- Intro Stat Computing and Data Management
This course teaches the ability to effectively manage and manipulate data, conduct statistical analysis and generate reports and graphics, primarily using the SAS Statistical Software package.
STA 506- Mathematical Statistics II
Continuation of STA 505. Correlation, sampling, tests of significance, analysis of variance, and other topics.
STA 505 - Mathematical Statics
A rigorous treatment of probability spaces and an introduction to the estimation of parameters.
STA 503 - Introduction to R
This is an introductory course in R programming. The major topics include setting up Rstudio, R data objects, data input/output, built-in and user-defined R functions, control statement and looping, basic R plot functions, commonly used R libraries, and R markdown.
STA 502 - Introduction to Python for Statistics and Data Science
In this course, students will learn to install Python and Jupyter Notebook, basic syntax, data input/output, control flows, data visualization and manipulation, along with basic descriptive statistics and statistical tests. They will also learn how to use some common libraries such as NumPy, Pandas and Maplotlib. This course will focus more on using Python as a tool for Statistics and Data Science rather than the intricacies of using an object-oriented programming language.
STA 490 - Capstone Course in Statistics
Course will synthesize lessons learned throughout the students career with the goal of preparing students for work as professional statisticians. Topics will include report writing, presentations, statistical consulting, sampling design, and resume writing.
STA 419 - Basics of Statistical Learning
This course will provide an introduction to statistical learning and predictive modeling. Tools will be developed for visualizing and understanding complex data sets. All data analysis will be done using the statistical programming language R.
STA 321 - Topics in Advanced Statistics
Course will cover select topics in categorical analysis, nonparametrics and time series analysis. Emphasis will be placed on statistical programming, particularly simulations.
STA 320 - Experimental Design
The purpose of this course is to guide students in learning how to design, conduct and analyze the results of scientific studies so that valid and objective inferences about the population are obtained. It will cover ANOVAs, block, factorial, and split plot designs, as well as response surface analysis.
STA 311 - Intro Statistical Computing and Data Management
Course will give students the ability to manage and manipulate data effectively, conduct basic statistical analysis, and generate reports and graphics primarily using the SAS Statistical Software Program.