Exploratory analysis of text data from blogs, news, and Twitter with plans for a text prediction algorithm and Shiny app.

Data: Obesity data.csv Info: Hồi quy tuyến tính; Hồi quy đa thức; Đánh giá relative importance; Tìm mô hình tối ưu bằng BMA package.

A 5-slide reproducible pitch for a Shiny application that predicts car mileage using horsepower and weight.

© 2026 Ayomide Hannah Igbaroola. All rights reserved. This R script accompanies the research article “How Does Water Footprint Labelling Shape Purchasing Intention For Low Water Footprint Food Products? A Case Study Of Polish Consumers” and may be used for personal, educational, or non-commercial purposes only.

A comprehensive R tutorial on applying Survival Analysis to sports data, moving beyond simple binary classification for injury prediction. This analysis simulates a 25-man football squad over 4 seasons to model the "time-to-event" for non-contact soft tissue injuries. It covers the creation of Kaplan-Meier survival curves, multivariate Cox Proportional Hazards regression, and the interpretation of Hazard Ratios to quantify the cost of workload and squad rotation.

This presentation pitches a data product designed for the Coursera Data Science Capstone. It outlines the development of a next-word prediction algorithm using N-gram modeling and a "Stupid Backoff" strategy. The project demonstrates the full data science pipeline: from exploratory analysis of a 4-million-line corpus (Twitter, News, Blogs) to the deployment of a reactive Shiny application. The focus is on balancing computational speed with predictive accuracy for mobile-first environments.