32443 - Statistical Methods for Data Analysis

Course Unit Page

Academic Year 2018/2019

Learning outcomes

The aim of the course is to make the students able to coherently use some statistical techniques for the analysis of multivariate data. The procedures covered in the course include:

- Introduction to multivariate analysis
- Multiple regression;
- Chi-square test
- T-test
- Principal components analysis
- Factor analysis.

Course contents

1. Introduction to multivariate statistical analysis.
2. Multiple linear regression: model specification, parameters estimation, residual analysis.
3. Chi square test for independence
4. T-test to compare means
5. Principal components analysis.
6. Factor analysis.

Readings/Bibliography

Inference:
Borra, Di Ciaccio (2014) Metodologie per le scienze economiche e sociali, 3^ edizione, Milano, McGraw-Hill education: chapters 8-14

Regression model:
Borra Di Ciaccio (2014): chapters 16-17

Multiple regression model (on-line): http://www.ateneonline.it/borra3e/capitolo_19%20new.pdf e http://www.ateneonline.it/borra3e/capitolo_21.pdf

Chi-square test and T-test:
Slides online

Principal components analysis and Factor analysis:
Slides online

Teaching methods

- Lectures, during which theoretical concepts as well as statistical techniques are explained and illustrated by examples.
- Tutorial sessions in computer laboratory.

Assessment methods

Written test and oral examination.

Office hours

See the website of Alessandro Lubisco