Teaching code

4S008094

Teacher

Coordinator

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

SECS-S/03 - ECONOMIC STATISTICS

Period

Primo semestre (lauree magistrali) dal Oct 3, 2022 al Dec 23, 2022.

Lessons timetable Moodle Seminars 0

Learning objectives

The course aims to provide the basic knowledge for the collection, management and analysis of data of interest in the managerial field. Students' previous statistical knowledge will be integrated with the main statistical sampling techniques for data collection, some of the most widespread techniques for the analysis of time series data, the multiple linear regression, and the most recent techniques for data science in the business context. All these techniques will be discussed in specific areas of application: market research, customer analysis, management control, production process control, sales analysis and forecasting. Special attention will be devoted to some of the most widespread software for data science and business intelligence. At the end of the course, students should demonstrate a good level of understanding both theoretically and practically of the main statistical methods for the analysis of business phenomena, in the light of the available data and the managerial needs. They should also be able to interpret critically the gathered information and the results obtained from the analyses with the aim to supply useful suggestions in support of business decisions.

Prerequisites and basic notions

Students are supposed to have acquired statistic knowledge of basic concepts provided in the bachelor degree in economics.

Program

1) Data sources:
Primary and secondary data.
Internal and external data sources.

2) Probabilistic and non-probabilistic sampling for sample survey:
Review of estimation theory.
Probabilistic sampling design.
Probabilistic sampling for variables.
Determination of the sampling size.

3) Customer analysis:
Pareto chart.
Concentration analysis. The Gini coefficient.

4) Statistical Analysis of sales data. Time Series analysis:
Time series decomposition in trend, seasonality and error.
Moving averages method.

5) Introduction to statistical quality control:
Statistical process control.
Control charts for variables.

6) Introduction to Business Intelligence. Techniques of data visualization.



The course is taught by lectures.
Lecture slides and other learning materials are available on the e-learning website.

Bibliography

Didactic methods

The course is taught by lectures.
Lecture slides and other learning materials are available on the e-learning website.

Learning assessment procedures

The assessment of learning outcomes consists in a two-hour written examination.

Evaluation criteria

Ability to understand the problems and to analyze them by choosing and applying the appropriate statistical method.
The exam is structured as follows: - 9 QUESTIONS WITH MULTIPLE ANSWERS concerning theoretical aspects of the program (up to 9 POINTS, out of 30) - 3 EXERCISES with numerical calculations of application to concrete cases of the analysis techniques learned during the course (up to 21 POINTS, out of 30).
If the written test is sufficient, there will be the possibility, at the discretion of the teacher or at the request of the student, to take an oral test as well.

Exam language

Italiano