A modern Fortran statistical library.

Fortran Statistics and Machine Learning Library

Significant Network Interval Mining

Customer base analysis is concerned with using the observed past purchase behavior of customers to understand their current and likely future purchase patterns. More specifically, as developed in Schmittlein et al. (1987), customer base analysis uses data on the frequency, timing, and dollar value of each customer's past purchases

This repository is a fork of a repository originally created by Lucas Descause. It is the codebase used for my Master's dissertation "Reinforcement Learning with Function Approximation in Continuing Tasks: Discounted Return or Average Reward?" which was also an extension of Luca's work.

Analysis of 2.2 million Realtor.com listings using Python and machine learning to uncover U.S. real estate market patterns. The project identifies market segments, predicts property prices, and reveals regional trends, providing data-driven insights for real estate professionals and investors.

Yeast TMT data - 3 different carbon sources (from Gygi lab) analyzed with PAW pipeline and MaxQuant

Multivariate analysis (MVA) of high dimensional heterogeneous data

MATLAB functions for Beta distribution test

This repository will include Python | Jupyter-Notebook statistical testing | tests and analysis. Highly useful for in depth data analysis & model development.

Statistical Modelling and Data Visualization of a Climate Change Dataset (January 1984 to December 2008 ) Sourced from Kaggle

GUI app for doing sliding window Z-score transformations of quantitative proteomics data

A/B Testing Analysis on Marketing Campaigns

This repository contains all about the proposed solutions to the assignments that I was required to complete as part of the Quantium Data Analytics Virtual Experience Program. 📊📈📉👨‍💻

Analysis of proportions using Anscombe transform

Binomial test implementation in Rust

A group seminar analyzing the relationship between citizens' average height and a country's Olympic success. The project involved data collection, descriptive statistics and statistical testing. Created and presented as part of the mandatory undergraduate Statistics course in spring 2021.

Quantium Virtual Experience Program hosted by Forage