This report analyzes two financial datasets using data science methods in R. The first dataset focuses on regression analysis to examine factors related to loan amounts, while the second dataset focuses on classification analysis to predict credit card default behavior. The report includes data cleaning, summary statistics, histogram analysis, log transformations, and theoretical distribution analysis.

R Markdown notebook implementing a full lipidomics pipeline on MTBLS4461 (MetaboLights). Covers data acquisition, QC, PQN normalisation, KNN imputation, PCA, and differential abundance testing by diabetes status and gender using limma eBayes.

A shiny application that calculates BMI using weight and height inputs.

Training in R for Data Science

Market Basket Analysis - Grocery Dataset_Apriori