Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Laurea magistrale in Marketing e comunicazione d'impresa - Enrollment from 2025/2026The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
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2° Year activated in the A.Y. 2022/2023
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Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Business Statistics (2021/2022)
Teaching code
4S00522
Teacher
Coordinator
Credits
9
Language
Italian
Scientific Disciplinary Sector (SSD)
SECS-S/03 - ECONOMIC STATISTICS
Period
primo semestre (lauree magistrali) dal Oct 4, 2021 al Dec 17, 2021.
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.
Program
Data sources and statistical information for business:
- primary and secondary data
- internal and external sources of data
- probabilistic sampling for market survey
Economic and business indicators:
- simple and composite index numbers
- nominal and real change of economic variables
- transition matrices and career transition measures
Time series analysis and forecasting:
- smoothing techniques: moving averages and exponential smoothing
- structural decomposition of economic time series
Introduction to statistical quality control:
- process capability ratios
- control charts for variables
Multivariate statistical analysis for business data and company business performances:
- simple linear regression models
- multiple linear regression models
- logistic regression models
- principal components analysis
Statistical learning for business:
- goodness of fit and cross-validation of statistical models
- classification and regression trees
- introduction to cluster analysis
Lecture slides and other learning materials are available on the e-learning website.
Bibliography
Examination Methods
The assessment of learning outcomes consists in a written examination.
Examination purposes
The written examination assesses the level of knowledge of the course topics, the ability to apply statistical methods for business and the interpretation of results.
Structure of the examination
The examination consists of single and multiple choice questions, questions which requires a numerical response, and open-ended questions. All kinds of questions may be focussed on theoretical and methodological issues, may consist in exercises, or may require the student to discuss and analyse some practical problem using notions and tools learned throughout the course.
The teacher may require students to take an oral examination which completes the evaluation of the acquired knowledge. The final grade may be equal, higher or lower than the grade got on the written part of the exam.
Assessment criteria
The examination score is on a 30-point scale (passing mark: 18).
