Scientific Disciplinary Sector (SSD)
SECS-S/03 - ECONOMIC STATISTICS
primo semestre magistrali dal Sep 30, 2019 al Dec 20, 2019.
During the course, the main sources of official data will be studied and the main sampling techniques analyzed. The linear regression model will be introduced as one of the main statistical tools to examine survey data and for sales forecasting. Students will be provided with the cutting-edge statistical theory of sampling and linear regression model. These tools will then be applied to carry out market researches.
1. Market research:
- Definitions, purposes and limits.
- Case studies related to market research
- Statistical methods for market research
- The main steps of a market survey.
2. Data sources for market surveys
- Primary and secondary data sources.
- Secondary data sources: internal and external
- Official statistical data.
- Main databases for marketing research(Infocamere, Cerved, AIDA, ecc.)
- Agency data (GfK-Eurisko, ACNielsen Italia)
- Panel surveys
3. Random and non-random sampling designs
- Review of estimation theory
- Definition of sampling design
- Random sampling designs
- Non-random sampling designs
- Sampling and non-sampling errors
4. Questionnaire construction and interviewing techniques.
- Self-administered questionnaires
- Assisted interview
- Computer-assisted personal interview
- Web interview
5. The regression model for marketing and sales forecasting
- Simple regression model: definition and hypotheses
- Parameter estimation and tests
- Residual analysis
- Goodness of fitting
- Estimation of trend using polynomial functions
- Polynomial degree choice
- Sales forecasting using the regression model
The interaction with students will be encouraged by discussing real business cases. Students are also expected to present short business cases through the solution of exercises. All slides projected during lessons will be made available on the e-learning platform before the beginning of the course. For this reason, students are strongly invited to register to the e-learning page of the course. Lectures will be recorded. Videos will be made available the next few days to allow students to revise or to attend lessons to which they have not been able to join directly. The availability of videos is also extended to all students who are unable to attend for work reasons or because they are abroad within the Erasmus program.
- Bassi F. (2009, I Ristampa), Analisi di mercato: Strumenti statistici per le decisioni di marketing (Edizione I), Carocci editore.
- Bracalente B. , M. Cossignani, A. Mulas (2009), Statistica Aziendale, McGraw-Hill.
- Biggeri Luigi , Matilde Bini , Alessandra Coli , Laura Grassini , M. Maltagliati (2017), Statistica per le decisioni aziendali. Ediz. mylab. Con eText, edito da Pearson Education Italia.
||Analisi di mercato: Strumenti statistici per le decisioni di marketing
|B. Bracalente, M. Cossignani, A. Mulas
|Biggeri Luigi , Matilde Bini , Alessandra Coli , Laura Grassini , M. Maltagliati
||Statistica per le decisioni aziendali. Ediz. mylab. Con eText
||Pearson Education Italia
Both the student's preparation will be evaluated as well as its ability to interpret and evaluate the results of the analyses based on the topics taught during the course.
The written test is compulsory. The structure of the test is as follows:
- one open question (up to 10 points, out of 30),
- two numerical exercises (up to 20 points, out of 30). Data will be provided for the solution of real case-studies using the basic tools learned during classes.
The oral test is optional.
Optional activity (attending students only)
Every attending student is given the opportunity to solve an exercise on the topics illustrated in the classroom. Students could ask the teacher to solve an exercise in front of the other students about the topics studied during the course. The interested students are kindly asked to contact the main instructor of the course.
The score (up to 2 points) will be added to the score of the written test.
The procedure is as follows:
- Reservation by students is done by sending an e-mail to the teacher. The deadline will be announced during classes.
- The student is given an exercise by the teacher. Presentation of the solution will start in November 2019.
- The presentation of the solution is delivered in the classroom using power point.