STATISTICAL TOOLS FOR MARKETING DECISIONS (MOD. I)
Objectives of the course
The course aims to provide several statistical models to assess performances evaluation, by focusing statistical and business features. The course is coherent with the requirements for the Master’s Degree in Quantitative Methods, and covers both hypothetical and actual case studies. Some business studies cases are also treated.
Expected learning outcomes
Knowledge and understanding skills. The course intends to give the instruments required to analyse statistical models for performance evaluation. The student will be able to analyse several online data warehouses, by using appropriate statistical methods, and observing both Italian and European scenario from an original point of view.
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 thorough 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 will help student pass the final exam.
Lifelong learning skills. Learning skills will be stimulated through power point 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.
General knowledge and reasoning ability. 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" section mentioned above.
The course is organised as follows:
Section 1 reviews statistical methods for assessing business performance (8 hours; 1 credit - ECTS/CFU).
Section 2 combines efficiency and productivity (8 hours; 1 credit - ECTS/CFU )
Section 3 considers the efficiency measures and the nonparametric approach to estimating technical efficiency (Data Envelopment Analysis - DEA). The parametric approach (16 hours; 2 credits - ECTS/CFU)
Section 4 concerns the productive activity structure and the recent features related to the multivariate statistical analysis of financial ratios (8 hours; 1 credit - ECTS/CFU).
Section 5 deals with several data warehouses for the quantitative analysis of economic phenomena, by using relevant statistical packages (8 hours; 1 credit - ECTS/CFU).
During the lessons the issues mentioned in the study program will be discussed and presented, together with applications by using statistical software. Slides and supplementary material can be downloaded from the Moodle platform.
Textbooks and supplementary suggested readings
Bracalente B., Cossignani M., Mulas A. (2009), Statistica aziendale, McGraw Hill.
Giovannini E. (2008), Understanding Economic Statistics: an OECD Perspective, OECD
Zhu J. (2015), Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets, 2nd edition, Springer.
Slides and supplementary material.
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 written exam will be organised in two sections, and students must be able to use the statistical packages in order to pass the exam. 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) analyze 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
- Evaluation of the level of understanding in the classroom during student presentations and exams given throughout the course
- Final written and oral examinations
- The written exam will be given on the computer. Students must be able to use the statistical packages in order to pass the exam.
Department of Management and Quantitative Studies
University of Naples " Parthenope " - Palazzo Pacanowski (ex Telecom)
Via Generale Parisi, 13. I - 80132 Napoli
IV floor - Room 432