Master’s degree in Marketing and Corporate Communication

Business Statistics

Course code
4S00522
Name of lecturer
Luigi Grossi
Coordinator
Luigi Grossi
Number of ECTS credits allocated
9
Academic sector
SECS-S/03 - ECONOMIC STATISTICS
Language of instruction
Italian
Site
VERONA
Period
primo semestre (lauree magistrali) dal Oct 5, 2020 al Dec 23, 2020.

Lesson timetable

Go to lesson schedule

Learning outcomes

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.

Syllabus

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. Face-to-face classes are possible following the general rules given by the University. During Covid-19 emergency, classes will be made available on streaming and recorded.

Suggested books
- 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.

Reference books
Author Title Publisher Year ISBN Note
Francesca Bassi Analisi di mercato: Strumenti statistici per le decisioni di marketing (Edizione 2) Carocci editore 2009 978-88-430-4427-6

Assessment methods and criteria

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 structure of the written 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.

Exams will be in face-to-face mode. However, the remote mode is possible for all students upon request during the academic year 2020-21.


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