BUSINESS DATA ANALYSIS

Academic year
2019/2020 Syllabus of previous years
Official course title
ANALISI DEI DATI AZIENDALI
Course code
ET0001 (AF:321017 AR:151263)
Modality
On campus classes
ECTS credits
6
Degree level
Bachelor's Degree Programme
Educational sector code
SECS-S/03
Period
3rd Term
Course year
3
This course provides some relevant statistical tools for exploratory data analysis and model estimation in Marketing quantitative research. Case studies in Marketing research will be discussed.
1. Knowledge and understanding:
1.1 Ability to collect and process qualitative and quantitative data;
1.2 Ability to deal with Gaussian, t-Student and Binomial variables;
1.3 Abilty to deal with basic statistical inference problems.

2. Applying knowdledge and understanding
2.1 Ability to select a probabilistic sample.
2.2 Ability to build, estimate and verify adeguate statistical models (regression and logit models)

3. Making judgements
3,1 Ability to suggest adeguate statistical models useful in corporate decisions ;
3.2 Ability to provide statistical analysis and economic-financial interpretation of business cases.
Knowledge of descriptive and inferential statistical techniques.
1. Introduction to principal aspects of finite population sampling.
The steps of the statistical analysis.
Statistical sampling techniques: random, non random.
Error measure (notions).

2. Statistical data analysis, data matrices.

3. Some important statistical sources for the business problems.
The survey on the Italian households' monthly expenditures (ISTAT Italian Central Bureau of Statistics) and the ACNielsen survey. The survey on the income (Bank of Italy).

4. Analysis of demand and forecasting.
Multiple regression.
Analysis for qualitative variables: logistic regression.
Notes by the teachers.
Brasini S., Tassinari F. (2000), Tassinari G., Marketing e pubblicita'. Metodi di analisi statistica, 2^ edizione. Il Mulino, Bologna, (capp. I-II-III).
Piccolo D. (1998), Statistica, Il Mulino, Bologna, (cap. XX-XXII-XXIII)
Riani M., Laurini F. (2007), Modelli statistici per l'economia con applicazioni aziendali, Pitagora Editrice Bologna.
Grading is based on written and oral exam. Written proof consists of applying statistical analysis techniques to dataset collected by the students. Oral proof consists in the results discussion.
Lectures and practice sessions.
Italian
Accessibility, Disability and Inclusion

Accommodation and support services for students with disabilities and students with specific learning impairments



Ca’ Foscari abides by Italian Law (Law 17/1999; Law 170/2010) regarding support

services and accommodation available to students with disabilities. This includes students with

mobility, visual, hearing and other disabilities (Law 17/1999), and specific learning impairments (Law 170/2010). If you have a disability or impairment that requires accommodations (i.e., alternate testing, readers, note takers or interpreters) please contact the Disability and Accessibility Offices in Student Services: disabilita@unive.it.
written and oral
Definitive programme.
Last update of the programme: 13/05/2019