90559 - Basic Analytics

Course Unit Page

SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Quality education Decent work and economic growth Reduced inequalities

Academic Year 2021/2022

Learning outcomes

Student is expected to get a basic knowledge and precise framework about statistics and statistical techniques concerning the analysis of data bases. In particular the student is expected to learn: - probability' s tools - measures of variance - index numbers.

Course contents

1. Data collection, management and visualization

2. Descriptive statistics

3. Foundations of probability

4. Statistical inference

4.1 Sampling

4.2 Estimation

4.3 Hypothesis testing

5. Simple regression

Readings/Bibliography

Suggested book

Luca Trapin, Lecture Notes for Basics Analytics.

Gary Smith, Essential Statistics, Regression, and Econometrics, Academic Press (Elsevier).

David Spiegelhalter, The Art of Statistics: Learning from Data, Pelican Book.

Teaching methods

Class lessons

Assessment methods

Written examination: theoretical questions and exercises

Grading system:

  • <18: fail
  • 18-23:sufficient
  • 24-27: good
  • 28-30: very good
  • 30 e lode: excellent

 

Teaching tools

Class notes on IOL

Office hours

See the website of Luca Trapin