Project Portfolio

(Links contain PDF project files)

1. Predicting Credit Card Fraud using Python

Given a dataset containing all credit card purchases on the west coast, we analyzed the data to pinpoint fraudulent transactions, determine the most common trends, and get to the bottom of this criminal activity. The goal was to strengthen fraud detection parameters for the credit card company.

Predicting Credit Card Fraud

2. Regression Model in R to Determine Various life stresses on Depression in Adults

Given a dataset, with 1 dependent variable and multiple independent variables, I fit a regression model in R on 24 Independent predictor values that tested why stressful experiences lead to depression in some people but not others. The dependent variable was the level of depression in adults based on our 24 independent variables. These independent variables were a variety of geneotype and environmental predictors, and we fit the model using stepwise regression to obtain the most significant fit.

Model of Life Stresses on Depression

3. Data Analyst Certification SQL/Python

Given a dataset from a restaurant chain containing food poisoning claims from several restaurants, I cleaned and verified the data using Python, then analyzed using SQL to draw insights on these claims and the time it takes to close each claim by restaurant location. Then presented my findings to the company lawyers using visualization in Python.

Certification

Data Analyst Associate Analysis

4. Single Predictor Linear Regression in R

Given a dataset in R, I merged files containing multiple variables, dealt with and imputed missing data, Transformed data to fit a linear regression and applied an approximate lack of fit test. We compared results of the Exponential model (DV=ln(y)), the Quadratic model (dv=sqrt(y)), the Reciprocal model (DV=1/y), the Logarithmic model (IV=ln(x)), and the Power model (DV=ln(y), IV= ln(x)) and found the power model to be the best fit Resulting in the highest R-squared value.

Linear Regression in R

5. UFC Championship Fighter Statistics

I personally logged the statistics of all current UFC champions (as of 10/10/2023), taken from ufcstats.com, and analyzed the data using Python. I then created this UFC Champion statistics booklet for the champion in each weightclass including pictures and statistical insights on each fighter.

UFC Champions Statistics