Creare un modello statistico in grado di prevedere con precisione il peso dei neonati alla nascita, basandosi su variabili cliniche raccolte da tre ospedali. Il progetto mira a migliorare la gestione delle gravidanze ad alto rischio, ottimizzare le risorse ospedaliere e garantire migliori risultati per la salute neonatale.

Develop an R function to draw a density curve representing the probability function of a continuous variable, with separate curves for each group, using ggplot2

This project explores a real estate dataset from Taiwan, applying exploratory data analysis and multiple linear regression models to understand the factors affecting housing prices per square meter. We visualize key relationships through scatterplots, histograms, and boxplots, and evaluate several regression models with increasing complexity. Model performance is assessed using R² and SSE metrics, while we also discuss important statistical assumptions such as normality and homoscedasticity. The analysis concludes with a comparison of the models and the selection of an optimal one for price prediction.