The course aims to provide the necessary tools for the design, processing and analysis of data in the field of management. The course introduces the student to statistical methodologies for market research, satisfaction analysis and business decisions. The theoretical part will be accompanied by a part applied to real data and case studies from marketing and management through the use of appropriate statistical software (such as Minitab, SPSS).
Students will be taught not only the theoretical aspect of the models but also the main application contexts and their use through appropriate statistical software.
The course in Statistics for Management teaches how to manage a statistical survey from its planning to the analysis and commentary of data.
Students will be taught not only the theoretical aspect of the models but also the main application contexts and their use through appropriate statistical software.
The course in Statistics for Management teaches how to manage a statistical survey from its planning to the analysis and commentary of data.
teacher profile teaching materials
- Hypothesis test on a parameter (mean, proportion, variance)
- Hypothesis test for the difference between means and proportions in the case of independent and paired samples
- independence tests
- Variance Analysis (ANOVA)
- Non-parametric tests (Wilcoxon, Mann-Whitney, Kuskal-Wallis, Spearman sign tests)
- Simple and multiple linear model
- Factorial analysis
- Cluster analysis
- Logistics regression
- Elements of sampling techniques and websurvey
Zani S., Cerioli A. (2007) Analisi dei dati e data mining per le decisioni aziendali, Giuffrè Editore.
Notes and handout (in Italian) are available at the web page of the course.
Programme
- Recalls of basic statistics and statistical inference- Hypothesis test on a parameter (mean, proportion, variance)
- Hypothesis test for the difference between means and proportions in the case of independent and paired samples
- independence tests
- Variance Analysis (ANOVA)
- Non-parametric tests (Wilcoxon, Mann-Whitney, Kuskal-Wallis, Spearman sign tests)
- Simple and multiple linear model
- Factorial analysis
- Cluster analysis
- Logistics regression
- Elements of sampling techniques and websurvey
Core Documentation
Agresti A., Finlay B.(2015) Metodi statistici di base e avanzati, Pearson EditoreZani S., Cerioli A. (2007) Analisi dei dati e data mining per le decisioni aziendali, Giuffrè Editore.
Notes and handout (in Italian) are available at the web page of the course.
Type of delivery of the course
The course includes 6 hours per week of classes by the lecturer; part of them are held in the computer lab. Since 5 March 2020, face-to-face lessons have been suspended as a consequence of the COVID19 emergency. The course continued as an on-line course.Type of evaluation
Examination procedure. The examination will take place orally as follows. Test for those carrying out the data analysis project The project is rated with a score from 0 to 3 points (3 points are given to projects carried out excellently). The project will be valid until the winter session included. The oral test will focus on the discussion of the project and the course program. The final grade will be given by the score of the individual oral examination to which the project score will be added. Test for those who do not carry out the data analysis project Extended oral examination on all the program. All students are kindly requested to read the procedures prepared by the University. In a session of 3 rounds, students can participate in a maximum of two rounds. Participating in the round means answering the appeal and handing in the written test (This rule shall be suspended until normal academic activity is restored.).