90909 - Workshop 2 (WS5)

Learning outcomes

The course aims at introducing students to the utilization of one of the main statistical packages for data analysis and presenting to them the basic elements of micro-data management and analysis. By the end of the course students will be familiar with the statistical package interface and be able to: load different types of data and different file formats into the statistical package, perform basic data management operations and conduct monovariate and multivariate statistical analyses using the software introduced during the course.

Course contents

DATA ANALYSIS WITH R - part I

This workshop is an introduction to Data Mining focusing on practical tools for Data Analysis and on the most used statistical learning techniques for numerical predictions.

Topics will be introduced theoretically but also tested in R-based softwares during the laboratory hours.

More in details, the course contents are:

• Introduction to Data Mining;
• Introduction to programming in R;
• Presentation of Exploratory Data Analysis tools and Regression algorithms for Big Data;
  
• Implementation of R scripts.

The module WS8 is designed as "part II", however its attendance is not mandatory for WS5 participants. 

Readings/Bibliography

Slides by the teacher.

James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). "An introduction to statistical learning" (Vol. 112, p. 18). New York: springer.

Teaching methods

Lectures and Laboratory lessons

Assessment methods

Evaluation of a laboratory project in R, with a final written report.

Teaching tools

Slides and script files by the teacher

Office hours

See the website of Elena Morotti