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
The 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 It will be activated in the A.Y. 2027/2028
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Two modules among the following| Modules | Credits | TAF | SSD |
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Two modules among the following| Modules | Credits | TAF | SSD |
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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.
Statistical methods and experimental design (2026/2027)
Teaching code
4S014043
Teacher
Coordinator
Credits
5
Language
English
Scientific Disciplinary Sector (SSD)
STAT-01/B - Statistics for Experimental and Technological Research
Period
Periodo generico dal Oct 1, 2026 al May 31, 2027.
Courses Single
Authorized
Learning objectives
The course aims to deepen the issues related to the design of experiments and data analysis (analysis of variance, linear regression). It also provides methodological tools that enable students to apply the acquired knowledge to oenological problems by identifying the most appropriate data analysis methodologies. By the end of the course, students will be able to apply statistical techniques to oenological issues, carry out quantitative analyses independently, and correctly interpret the results. They will also develop critical skills to assess collected information and provide valuable insights to support strategic decisions in the viticulture and winemaking sector, while acquiring the terminology necessary to communicate analytical results clearly and effectively.
Prerequisites and basic notions
No formal prerequisites are required.
Program
The course aims to deepen the issues related to the design of experiments and data analysis (analysis of variance, linear regression).
Course program:
1. Descriptive statistics, probability and inference.
Frequency tables and graphics. Mean, median and variance. Random variables and their distributions. Confidence intervals and testing hypotheses.
2. Relationships.
Pearson's independence test, correlation.
3. Linear regression.
Linear regression models. Inference on the parameters, Goodness of fit. Notes on multiple regression analysis.
4. Analysis of variance. Notes on Experimental design.
Bibliography
Didactic methods
Lectures.
Particular emphasis will be given to aspects of an applied nature, alternating, during the lessons, moments of a theoretical nature and exercises.
Learning assessment procedures
The exam aims to verify that the student has acquired the concepts presented during the course and is familiar with the tools proposed for data analysis and inferential procedures.
In particular, the exam consists of a written test that lasts 1 hour and 30 minutes and is divided into two parts. The first part involves carrying out a questionnaire lasting 30 minutes. The second one-hour part consists of exercises in a sufficient number to verify understanding of the program, each with its own score.
Evaluation criteria
The outcome of the test will be determined on the basis of knowledge of the contents proposed in the course and the ability to apply them.
Criteria for the composition of the final grade
The final outcome will be calculated by adding the scores obtained in the individual exercises and in the questionnaire.
Exam language
English
