Data Analysis (A.Y. 2023/24)

Project work

• The project work can be carried out individually or in group (2 students per group)

• Each group must find from 2 to 4 data sets of interest and analyze them

• The analysis should include techniques covering all the parts of the course (data set description, hypothesis testing, linear regression, classification)

• The outcome of the project work is a Jupyter Notebook containing the developed code and a discussion (with tables, graphs, plots, etc.) about

  • the aspects that have been analyzed (e.g., formulation of questions to be answered)

  • the obtained results (e.g., answers to formulated questions)

• The Jupyter Notebook must be turned in (via email) one week before the date of the oral exam (see below)

• Two weeks before the date of the oral exam (see below) each group must send me an email with the following information

  • name of the group members, together with their ID number (matricola)

  • link to the chosen data sets

  • brief description of the aspects that the students intend to investigate (e.g., formulation of questions to be answered)

Oral exam

• The oral exam includes a discussion about the project work and questions about the theory.

  • The discussion about the project work aims at verifying that students have correctly applied the studied methodologies and that they have correctly interpreted the obtained results. During the discussion, students may be required to write small pieces of code to investigate further aspects of the considered data sets.

  • Theoretical questions aim at verifying that students have acquired the basic notions of data analysis.

Calendar of the Fall exam session

• First exam slot

  • Date of oral exam

    • September 2

  • Deadline for turning in project work solution

    • August 26

  • Deadline for turning in data set and project work description

    • August 19

• Second exam slot

  • Date of oral exam

    • September 17

  • Deadline for turning in project work solution

    • September 10

  • Deadline for turning in data set and project work description

    • September 3