92987 - Basic Analytics (1) (Lm)

Academic Year 2025/2026

  • Docente: Luca Trapin
  • Credits: 6
  • SSD: SECS-S/02
  • Language: English

Learning outcomes

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
    --> Sampling
    --> Estimation
    --> Hypothesis testing

Readings/Bibliography

Textbook

Luca Trapin, Lecture Notes for Basics Analytics.

Additional Material (Optional)

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 Virtuale

Office hours

See the website of Luca Trapin