University classes

Statistics

Classroom | 2024-25

  • Primary language: Italian
  • Institution: University of Naples L’Orientale
  • Prerequisites: No formal prerequisites are required

Aim: This course aims to provide students with the knowledge and methodological tools necessary to critically analyze and evaluate results derived from data characterized by variability and uncertainty. By the end of the course, students should demonstrate independent judgment, communication skills, and the ability to learn independently. The course will focus on understanding the fundamental theoretical concepts of statistics (such as probability, variability, correlation, association, distribution, and statistical summary) and interpreting statistical summary indicators for the analysis and comparison of collective phenomena.

Content: The course provides students with fundamental knowledge of descriptive and inferential statistics, with a particular focus on the context of political science. By the end of the course, students will be able to appropriately address the variability and uncertainty of statistical data. Examples drawn from the socio-political and economic spheres will be used throughout the course.

Textbooks

Course Notes: Additional materials, articles, readings, and assignments will be provided on the online platform associated with the class.

Economic Data Analysis

Classroom | 2024-25

  • Primary language: Italian
  • Institution: University of Naples L’Orientale
  • Prerequisites: No formal prerequisites are required. However, it is recommended to have taken a basic statistics course

Aim: The objective of the course is to provide students with the basic knowledge needed to understand, analyze, and communicate real economic data, with a particular focus on their critical interpretation from political, social, and economic perspectives. In addition, students will be provided with the basic tools to use R in their future academic and professional projects.

Content: The course provides the fundamental tools for analyzing economic data through descriptive statistical methods and the use of statistical software. The topics covered focus on data interpretation, the construction of economic indicators (index numbers), and time series analysis. The practical component of the course involves using R software for data processing, visualization, and report generation.

Textbooks

Course Notes: Additional materials, articles, readings, and assignments will be provided on the online platform associated with the class.

Data Science Lab with R

Classroom | 2024-25

Note: To enroll the course it is mandatory to send an email specifying first name, last name, student ID, and course of study.
Enroll
  • Primary language: Italian
  • Institution: University of Naples L’Orientale
  • Prerequisites: No formal prerequisites are required. However, it is recommended to have taken a basic statistics course

Aim: The course is designed as a practical introduction to using R for students with no prior experience in programming. The approach will emphasize active learning, with a focus on acquiring skills useful for the job market or for potential future academic pursuits. The aim is to provide students with the basic tools to use R in their future academic and professional projects.

Content: Activities will be geared toward active learning, with concrete examples provided by the instructor, and will consist of i) data loading and preprocessing, ii) visualizing information in graphical format for interpretive purposes, and iii) understanding and applying simple statistical analyses to support research projects. By the end of the course, students will be able to independently analyze datasets, produce key descriptive statistics, and present results using reports and graphical tools. Assessment consists of developing individual or group projects to apply the knowledge gained.

Textbooks

Course Notes: Additional materials, articles, readings, and assignments will be provided on the online platform associated with the class.

Data Analysis with Python

Classroom | 2024-25

  • Primary language: Italian
  • Institution: University of Naples Federico II
  • Prerequisites: No formal prerequisites are required. However, it is recommended to have taken a basic statistics course

Aim: TBA

Content: TBA

Textbooks

Course Notes: Additional materials, articles, readings, and assignments will be provided on the online platform associated with the class.

Doctoral School Classes

Statistical Methods and Analysis of Textual Data

Classroom

  • Primary language: English
  • Institution: University of Naples L’Orientale

Content: TBA

Course Notes: Additional materials, articles, readings, and assignments will be provided on the online platform associated with the class.

Power analysis

Classroom

  • Primary language: English
  • Institution: University of Naples Federico II

Content: TBA

Course Notes: Additional materials, articles, readings, and assignments will be provided on the online platform associated with the class.

Past Teaching

A.Y. Course Language Institution
2022 - 2025 Statistical Quality Control Italian UniNA
2022 - 2024 Digital Transformation and Business Innovation: Data Science Module Italiano UniSOB
2022 - 2023 Statisic Lab Italian UniSOB
2021 - 2022 R and SAS Statistical Lab Italian UniNA
2021 - 2022 Statistics Italiano UniSOB
2020 - 2021 Statistical Methods for Economy Italian UniSANNIO
2019 - 2020 Statistics Part 2 English UniCAS
2018 - 2021 Statisic Lab Italian UniSOB
2018 - 2019 Statistics Italian UniCAS

Legenda. UniOR: University of Naples L’Orientale; UniNA: University of Naples Federico II; UniSOB: University of Naples Suor Orsola Benincasa; UniCAS: University of Cassino and Southern Lazio; UniSANNIO: University of Sannio.