| FINANCIAL REPORTING
(obiettivi)
LEARNING OUTCOMES:
The course provides an introduction to the modelling of economic and management variables using regression and multivariate methods, both in a parametric than a nonparametric framework; the emphasis is on business, marketing and industrial applications. The program will cover models for the analysis of dependence (linear regression, ANOVA, autoregressive model, logit and probit models) and exploratory techniques for data reduction (principal component analysis and clustering analysis).
KNOWLEDGE AND UNDERSTANDING:
Knowledge and understanding of parametric and nonparametric statistical techniques applied to marketing, sales and financial problems. At the end of the course students should be able to understand: (i) how to apply statistical models in a supervised and unsupervised approach; (ii) perfectly know the model’s assumptions and understanding of the tools needed to verify these hypotheses; (iii) understand the model selection techniques and measures of the model prediction capability. In particular, students will manage:
• Linear regression model
• Logit and Probit model
• Analysis of Variance
• Autoregressive model AR(1)
• Cluster Analysis
• Principal Component Analysis
APPLYING KNOWLEDGE AND UNDERSTANDING:
Practical evidence of the concepts will be given with examples using statistical software such as STATA and SAS applied on real datasets. The students will have to practice both in class that with homeworks on the use of specific software so to be able to comment and understand the output.
MAKING JUDGEMENTS:
Students will be able to choose the more appropriate statistical techniques and to select the right set of explanatory variables. On the basis of results obtained, they will be able to give an interpretation about the relationship between the variables under study.
COMMUNICATION SKILLS:
Students will be able to prepare statistical reports using graphs, tables, figures and commenting them.
LEARNING SKILLS:
Students will have access to reading and understanding scientific articles using the multivariate methods considered in the course program. They will be able to identify the most appropriate methods to answer specific research questions.
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