STATISTICAL METHODS FOR BUSINESS DECISIONS
Objectives of the course (Learning objectives / Target skills)
The course aims to provide several statistical models in order to assess business features. In detail, this course refers to the statistical methods to support the business decision making. The Microsoft Excel tools, its add-ins and several VBA procedures will be covered. SPSS software will be also considered. Both hypothetical and actual case studies will be fixed.
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 show the ability to (1) analyse several data warehouses throughout appropriate statistical methods, and (2) suggest some comments by using an original perspective.
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 consequences of the usage of different statistical approaches. The student will to be able to apply their skills in different scenarios.
Making judgements. The student will show the ability to understand simple and complex phenomena, by using indicators built on the available information. In more detail, the student will be able to analyse the relationships in a multidimensional scenario, by performing specific analysis throughout a statistical software.
Communicative Skills. At the end of the course, the student will be able to explain the results of the model throughout an appropriate terminology, in order to explain the results of his analysis. The presentation of several “case studies could help in a better understanding of the usage of different statistical tools.
Lifelong learning skills. Learning skills and autonomous investigations will be stimulated through (1) discussions among the students in the classroom and (2) lectures supported by power point slides. The analysis of some research articles (or essays) will increase the student’s background.
Prerequisite skills are the basic knowledge of descriptive and inferential statistics, in addition to mathematics. General knowledge and reasoning ability are also required. Students who lack the prerequisites for this course can refer to the professor who will supply a bibliography or supplementary contents
See "Contents" section mentioned above
Study program/ Contents.
The course is organised as follows.
Section I “Exploratory Data Analysis and Tools” refers to:
- Statistical Models (1 ECTS; 8 hours);
- Microsoft Excel advanced functions, procedures and its additional tools (1 ECTS; 8 hours);
- SPSS (1 ECTS; 8 hours).
Section II “Advanced statistical models and VBA data handling for problem solving” discusses:
- Linear Regression (1 ECTS; 8 hours).
- Cluster and Factor Analysis (2 cfu; 16 hours).
Course organization: traditional teaching.
During the lessons (48 hours in total) the issues mentioned in the study program will be discussed and presented. The evaluation of the level of understanding in the classroom during student presentations will be also considered. Slides and supplementary material can be downloaded from the Moodle platform.
Textbooks and supplementary suggested readings.
Slides and supplementary material.
CLEFF T. (2014), Exploratory Data Analysis in Business and Economics: An Introduction Using SPSS, Stata, and Excel, Springer.
NIGEL DA COSTA LEWIS (2004), Operational Risk with Excel and VBA: appllied Statistical Methods for Risk Management, Jhon Wiley and Sons [chapters 1-7].
Supplementary suggested readings
- BERENSON M.L., KREHBIEL T.C., VISWANATHAN P. K., LEVINE D. M., Business Statistics: A First Course - 5th English Edition [PHSTAT2 ADD IND]
The assessment is based on a written examination structured on thematic questions strictly connected to the study program, in order to test the results of the students achievements. An oral examination must also be held. Students have to be able to use the statistical packages in order to pass the exam. The oral examinations are held in public session. The exam involves an evaluation which is expressed with a grade out of 30. The exam is deemed to be passed successfully if the final grade is between 18 and 30. In the event of a full grade (30/30), the Examination Board may grant honours (lode).
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