This repository contains the code for the (group M) final project of A.Y. 2022-2023 Professor Nicola Torelli and Professor Gioia Di Credico's course on Statistical Methods for Data Science at the University of Trieste in the A.Y. 2022-2023.

It is required to analyze the Residential Building Data Set, containing data about Iranian real estate single-family residential apartments constructions building data.
More specifically, the request is to study possible statistical models to predict SalesPrice as response variable, given the other explanatory variables.

The project has been divided into sub-problems and resolved as follows:

• Enrico Stefanel (@enstit): problem statement, exploratory data analysis and data-cleaning phase;
• Cristian Curaba (@Cristian-Curaba): selection, description and comparison of most suitable models;
• Yaiza Martínez Jiménez: comments on results.

The .Rmd file contains all the project analysis. A rendered version of it can be found into the HTML file with the same name.
In order to successfully run all the code, you need to install some R packages (if not already installed on your system):

install.packages('dplyr', 'openxlsx', 'ggplot2', 'AER', 'MASS', 'car', 'boot', 'randomForest')