2. Professors
  3. RARITA' Luigi
  4. Teaching

STATISTIC AND DATA ANALYSIS

Luigi RARITA' STATISTIC AND DATA ANALYSIS

0222100174
DEPARTMENT OF MANAGEMENT & INNOVATION SYSTEMS
EQF7
BUSINESS MANAGEMENT AND CONSULTING
2025/2026

OBBLIGATORIO
YEAR OF COURSE 2
YEAR OF DIDACTIC SYSTEM 2023
SPRING SEMESTER
CFUHOURSACTIVITY
630LESSONS
LUIGI RARITA' T Curriculum
Objectives
GENERAL AIM
THE COURSE AIMS TO ACQUIRE THE BASIC ELEMENTS OF SAMPLING THEORY, WITH EMPHASIS ON ADVANCED TOOLS OF INFERENTIAL STATISTICS. THE EDUCATIONAL AIMS OF THE COURSE CONSIST IN THE ACQUISITION OF TECHNIQUES AND TOOLS TO ANALYSE POPULATIONS UNDER INVESTIGATION, AS WELL AS THE ABILITY TO DERIVE FORECASTS ON MARKET PHENOMENA.

KNOWLEDGE AND ABILITY TO UNDERSTAND
THE TEACHING PROMOTES A QUANTITATIVE TRAINING WITHIN THE FIELD OF MARKETING AND MARKET ANALYSIS, WITH EMPHASIS TO THE COGNITIVE NEEDS OF BOTH PUBLIC AND PRIVATE COMPANIES. IN PARTICULAR, THE MAIN SAMPLING AND INFORMATION COLLECTION TECHNIQUES WILL BE SHOWN VIA THEORETICAL DEVELOPMENTS AND EMPIRICAL EVIDENCE. THROUGH THE EXPERIENTIAL LEARNING, THE PERFORMANCE OF DIDACTICAL ACTIVITIES FORESEES WORKSHOPS AND PROJECT WORK TO STIMULATE THE ABILITY TO LEARN AUTONOMOUSLY AND LEARNING BY DOING.

ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING
SPECIFICALLY, THE TEACHING AIMS TO PROVIDE TO THE STUDENTS KNOWLEDGE AND COMPREHENSION SKILLS, INTEGRATED WITH THE PROVISIONS OF THE REFERENCE DEGREE COURSE VIA THE ILLUSTRATION OF TOOLS USEFUL TO:
•ACQUIRE USEFUL KNOWLEDGE TO PLAN AND REALIZE SAMPLE SURVEYS.
•KNOW THE MAIN SAMPLING PLANS, EVEN COMPLEX ONES, AND THEIR APPLICATION IN REAL CONTEXTS.
•ACQUIRE THE BASICS OF THE THEORY OF SAMPLES.
•KNOW THE MAIN METHODS TO ESTIMATE THE FEATURES OF THE POPULATION.
•KNOW THE MAIN INFORMATION GATHERING TECHNIQUES USEFUL FOR MARKET RESEARCH.

INDEPENDENCE OF JUDGMENT
THE STUDENT WILL BE ABLE TO:
•SOLVE PROBLEMS AND MAKE DECISIONS;
•FORMULATE REPORTS AND ASSESSMENTS ON THE BASIS OF LIMITED OR INCOMPLETE INFORMATION.

COMMUNICATION SKILLS
THE STUDENT WILL BE ABLE TO:
•COMMUNICATE USING COMPUTER TOOLS;
•TRANSMIT IDEAS, PROBLEMS AND SOLUTIONS;
•COMMUNICATE WITH STAKEHOLDERS.

LEARNING ABILITY
THE STUDENT WILL BE ABLE TO:
•PROCEED INDEPENDENTLY IN UPDATING KNOWLEDGE;
• EVALUATE THE CONTINUATION OF YOUR EDUCATION IN THE UNIVERSITY AND OTHERS.
Prerequisites
NONE. KNOWLEDGE OF MATHEMATICS AND STATISTICS CONTENT IS RECOMMENDED.
Contents
BASIC PRINCIPLES OF SAMPLING THEORY AND ESTIMATION THEORY (8 HOURS).
POPULATION, SAMPLE, AND SAMPLING DESIGN. PROBABILISTIC SAMPLING: SIMPLE RANDOM SAMPLING WITH AND WITHOUT REPLACEMENT. SAMPLING DISTRIBUTIONS: DISTRIBUTION OF THE SAMPLE MEAN, SAMPLE PROPORTION, AND SAMPLE VARIANCE. POINT ESTIMATORS: CHARACTERISTICS AND PROPERTIES; MAXIMUM LIKELIHOOD ESTIMATION. INTERVAL ESTIMATION: USEFULNESS FOR MARKET PHENOMENA; CONFIDENCE INTERVAL FOR THE VARIANCE OF A NORMAL POPULATION; CONFIDENCE INTERVAL FOR THE DIFFERENCE BETWEEN POPULATION MEANS.

INFERENCE-BASED DECISION-MAKING METHODS (6 HOURS).
HYPOTHESIS TESTING: NULL AND ALTERNATIVE HYPOTHESES; ACCEPTANCE AND REJECTION REGIONS FOR A HYPOTHESIS SYSTEM; TESTS FOR THE VARIANCE OF A NORMAL POPULATION; TESTS FOR THE ANALYSIS OF PAIRED AND INDEPENDENT SAMPLES; COMPUTATION OF THE P-VALUE; NUMERICAL AND GRAPHICAL APPROACHES FOR THE DEFINITION OF THE TYPE II ERROR FOR A GENERIC HYPOTHESIS SYSTEM.

ADVANCED SAMPLING AND INFERENCE TECHNIQUES (5 HOURS)
SYSTEMATIC SAMPLING. STRATIFIED SAMPLING: GENERAL CONCEPTS AND QUANTITATIVE ANALYSIS OF STRATA. CLUSTER SAMPLING. SAMPLING PLANS. SAMPLING METHODOLOGIES FOR STATUTORY AUDITING. ONE-WAY AND MULTI-WAY ANALYSIS OF VARIANCE: APPROACHES FOR SIMULTANEOUS COMPARISON OF MULTIPLE SAMPLES SUBJECTED TO DIFFERENT TREATMENTS; METHODOLOGIES FOR IDENTIFYING DIFFERENT TREATMENTS.

NUMERICAL METHODS FOR DATA ANALYSIS (11 HOURS)
SIMULATION OF SIMPLE RANDOM SAMPLING AND SYSTEMATIC SAMPLING APPROACHES. MULTIPLE LINEAR REGRESSION TECHNIQUES. PRINCIPAL COMPONENT ANALYSIS FOR BIG DATA. CLUSTER ANALYSIS: HIERARCHICAL AND NON-HIERARCHICAL METHODS. TIME SERIES ANALYSIS (OVERVIEW).
Teaching Methods
THE TEACHING FORESEES 12 HOURS OF THEORETICAL LESSONS AND 18 HOURS OF CLASSROOM EXERCISES, ESSENTIAL TO CORRECTLY INTERPRET THE ANALYZED MARKET PHENOMENA, ALSO WITH REFERENCE TO THE USE OF NUMERICAL TOOLS.
THE ATTENDANCE AT LECTURES AND EXERCISE SESSIONS, ALTHOUGH NOT MANDATORY, IS HIGHLY RECOMMENDED IN ORDER TO FULLY ACHIEVE THE LEARNING AIMS.
Verification of learning
THE ACHIEVEMENT OF THE TEACHING OBJECTIVES IS CERTIFIED BY PASSING AN EXAM WITH A GRADE OUT OF THIRTY WITH POSSIBLE LAUDE. THE EXAM CONSISTS OF A WRITTEN TEST AND AN ORAL TEST. THE WRITTEN TEST LASTS TWO HOURS AND IS STRUCTURED WITH THREE EXERCISES, COVERING ALL ASPECTS OF THE SYLLABUS. THE OUTCOME OF THE WRITTEN TEST IS “PASSED” OR “FAILED”.
STUDENTS WHO PASS THE WRITTEN TEST WILL HAVE TO TAKE AND PASS THE ORAL TEST. THE ORAL TEST, THAT FORESEES THE DISCUSSION OF A PROJECT WORK AND THEORETICAL CONTENTS, IS DESIGNED TO ASCERTAIN THE DEGREE OF KNOWLEDGE OF ALL TOPICS COVERED IN THE TEACHING.
THE FINAL GRADE IS DETERMINED AFTER THE OUTCOME OF THE ORAL DISCUSSION. IN EVALUATING THE EXAMINATION, KNOWLEDGE OF THE SUBJECT MATTER, EXPOSITORY ABILITY, ACCURACY OF LANGUAGE, AND THE ABILITY TO USE CRITICALLY THE MATHEMATICAL/STATISTICAL ACQUIRED TOOLS, WILL BE CONSIDERED.
LAUDE WILL BE AWARDED TO STUDENTS WHO DEMONSTRATE EXCELLENT KNOWLEDGE OF COURSE CONTENTS, OPTIMAL PRESENTATION SKILLS, AND HIGH MATURITY IN APPLYING THE ACQUIRED KNOWLEDGE TO SOLVE PROBLEMS NOT ADDRESSED DURING CLASSROOM LECTURES.
Texts
B. V. FROSINI, M. MONTINARO, G. NICOLINI: “CAMPIONAMENTI DA POPOLAZIONI FINITE. METODI E APPLICAZIONI”, G. GIAPPICHELLI EDITORE – TORINO, 2011.
F. MECATTI: “STATISTICA DI BASE – COME, QUANDO, PERCHÉ”, 3° EDIZIONE, MCGRAW HILL, 2022.
M. K. PELOSI, T. M. SANDIFER, P. CERCHIELLO, P. GIUDICI: “INTRODUZIONE ALLA STATISTICA – IMPARARE DAI DATI”, 3° EDIZIONE, MCGRAW HILL, 2025.
M. RIANI, A. CORBELLINI, F. LAURINI, G. MORELLI, T. PROIETTI, E. FIBBI, D. PERROTTA, F. TORTI, “DATA SCIENCE CON MATLAB”, G. GIAPPICHELLI EDITORE – TORINO, 2023.
SUPPLEMENTARY TEACHING MATERIALS WILL BE AVAILABLE IN THE TEACHING SECTION WITHIN THE UNIVERSITY’S E-LEARNING AREA (HTTP://ELEARNING.UNISA.IT), ACCESSIBLE TO STUDENTS IN THE COURSE VIA THE UNIQUE UNIVERSITY CREDENTIALS.
More Information
TEACHING IS PROVIDED IN ITALIAN.
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