Università degli Studi di Napoli "Parthenope"

Teaching schedule

Academic year: 
Belonging course: 
Course of Master's Degree Programme on MARITIME ECONOMY
Disciplinary sector: 
Year of study: 
First Semester
Hours of front activity: 



Course description

The course aims to provide several statistical models to assess transportation data analysis, according to the contents of the Degree Program.

In detail, this course refers to the statistical methods for support decision making in the transport sector.

Expected learning outcomes.

Knowledge and understanding skills.
The course intends to give the instruments required to analyse statistical models to support business decision making. The student will be able to analyse several online data warehouses by using appropriate statistical methods.

Applying knowledge and understanding.
The course aims to analyse several models for evaluation, also by using the appropriate statistical packages, in order to evaluate the main features of implications of the different statistical approaches .

Making judgements.
The student will be able to understand simple and complex phenomena, by using indicators built on the available information. In more detail, the student will be able to:
• study the relationships in a multidimensional scenario;
• apply several statistical methodologies;
• perform analysis through statistical software.

The presentation of several “case studies” could help in a better understanding of different statistical tools.

Communicative Skills.
At the end of the course, the student will be able to explain the results of the model through an appropriate vocabulary.
The presentation by PowerPoint slides of several case studies will help the student pass the final exam.

Lifelong learning skills.
Learning skills will be stimulated through PowerPoint presentations and discussions among the students in the classroom. Several presentations connected to previous researchers and the analysis of some scientific articles (or essays) will increase the student’s background


Prerequisite skills are the basic knowledge of descriptive and inferential statistics. Students who lack the prerequisites for this course can refer to the professor who will supply a bibliography or supplementary content.


See contents for more details.

Contents can be divided into six sections, as follows.

Section 1. Statistical data sources and data warehouse (2 ECTS credits; 16 hours)

Section 2. Statistical techniques and transport issues (1 ECTS; 8 hours)

Section 3. Technical performance (1 ECTS; 8 hours)

Section 4. Efficiency and productivity (1 ECTS; 8 hours)

Section 5. Measuring the efficiency: Data Envelopment Analysis (DEA); non radial DEA; Stochastic frontier analysis (SFA) (3 ECTS; 24 hours)

Section 6. Benchmarking and Multivariate models. (1 ECTS; 8 hours)

Teaching Methods

The course consists of traditional lectures (72 hours).

During the lessons, the issues mentioned in the study program will be discussed and presented, together with applications by using statistical software (SPSS, R, VBA ).
Slides and supplementary material can be downloaded from the Moodle – Parthenope University e-learing platform.


Slides and supplementary material (Moodle)


Washington S.P., Karlaftis M.G., Mannering F.L. (2011) Statistical and econometric methods for transportation data analysis. Chapman&Hall [pagine 1-62; 235-258; 403-489]

Bogetoft P., Otto L. (2011), Benchmarking with DEA, SFA, and R, Springer.

Zhu J. (2015), Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets, Springer.

Learning assessment

The assessment is based on a written examination composed of thematic questions on the study program, which are expressly aimed at testing the results of the students achievements. An oral examination must also be held. The oral examinations are held in public session. The exams involve an evaluation which is expressed as a grade of out of 30. An exam is deemed to be passed successfully if the final grade is equal to or higher than 18/30. In the event of a full grade (30/30), the Examination Board may grant honours (lode). Students who pass the exam will be able to analyse business phenomena by using appropriate statistical methods from an original point of view. They also will be able to (1) analyse output results obtained through statistical software, (2) apply their skills in different contexts (3) use the appropriate terminology to explain the results of the models and (4) share their experiences in the field.
Assessment methods in detail
- Lectures supported by power point slides
- Presentations of several case studies
- Presentations by the students in the classroom
Examination methods:
- Evaluation of the level of understanding in the classroom during student presentations and exams given throughout the course
- Final written and oral examinations. The exam must be completed in 1,5 hour.

- The written exam will be given on the computer. Students must be able to use the statistical packages in order to pass the exam.

More information


Academic address
Department of Management and Quantitative Studies [DISAQ]
University of Naples " Parthenope "
Palazzo Pacanowski
Via Generale Parisi, 13. I - 80132 Napoli
IV floor - Room 432

website: www.disaq.uniparthenope.it

Telephone+ 39 081 547 4266
Fax + 39 178 6001361
e-mail: paolo.mazzocchi@uniparthenope.it