DATA SCIENCE AND MULTIVARIATE STATISTICS

Course objectives

Provide the theoretical foundations and essential tools of data science and exploratory statistical analysis. In particular: Knowledge and understanding Data science and exploratory statistical analysis; Data matrix and data pre-processing; Proximity matrix; Covariance matrix and correlation matrix; Cluster Analysis; Principal Components Analysis. Ability to apply knowledge and understanding Ability to choose and apply the statistical methodologies learned in the business and economic fields. Autonomy of judgement Independent ability to collect and process data and interpret results Communication skills Ability to clearly present the results of the statistical analyzes carried out Learning ability Ability to learn new statistical techniques independently

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PIERPAOLO D'URSO Lecturers' profile

Program - Frequency - Exams

Course program
1. Informational paradigm (information, knowledge, decision-making) 2. Data science and exploratory analysis 3. Data matrix and data pre-processing. 4. Proximity matrix 5 Covariance matrix and correlation matrix 6. Cluster Analysis. 7. Principal Component Analysis.
Prerequisites
Basic statistics
Books
TEACHING NOTES
Frequency
Strongly recommended attendance.
Exam mode
Written exam (exercises). The test is intended to assess knowledge and understanding and the student's ability to apply knowledge and understanding. In itinere evaluation will be performed, based on two tests with the same structure and rules.
Lesson mode
Lectures, exercises.
PIERPAOLO D'URSO Lecturers' profile

Program - Frequency - Exams

Course program
1. Informational paradigm (information, knowledge, decision-making) 2. Data science and exploratory analysis 3. Data matrix and data pre-processing. 4. Proximity matrix 5 Covariance matrix and correlation matrix 6. Cluster Analysis. 7. Principal Component Analysis.
Prerequisites
Basic statistics
Books
TEACHING NOTES
Frequency
Strongly recommended attendance.
Exam mode
Written exam (exercises). The test is intended to assess knowledge and understanding and the student's ability to apply knowledge and understanding. In itinere evaluation will be performed, based on two tests with the same structure and rules.
Lesson mode
Lectures, exercises.
  • Lesson code10606758
  • Academic year2025/2026
  • CourseEconomics and policies for global sustainability
  • CurriculumSingle curriculum
  • Year1st year
  • Semester2nd semester
  • SSDSECS-S/01
  • CFU6