Computer Skills, Statistics and Data Management in the Winery
A.Y. 2024/2025
Learning objectives
The contribution of course to the achievement of the educational objectives of the bachelor degree consistently with the professional profiles and employment opportunities provided for the entire training course consists in the acquisition of the ability to consult bibliographic and thematic databases, and in the to collect the essential information for the technical description of the related environmental, structural and managerial characteristics preparatory for their critical evaluation. To acquire the knowledge of descriptive and inferential statistics, essential for the description of biological phenomena and the evaluation of simple viticultural experiments, in an integrated vision, having obtained the computer skills needed for their synoptic and graphic representation.
Expected learning outcomes
At the end of the course, the student will have adequate knowledge of the most popular database management software, as well as the notions for effective querying of search engines to find information. He/she will also have acquired adequate knowledge of descriptive statistics and elements of inferential statistics; an adequate ability to produce technical report in synoptic and graphic form. Furthermore, the student will acquire the ability to approach a technical-scientific report documented as a final dissertation or a technical report, with reference to the vinicultural farm, in relation to the environmental (geographical and pedoclimatic), land (land and buildings) and management description (genetic resources, plants, machinery and technical tools), and the critical description of the production processes in the vineyard and in the winery.
Lesson period: Second semester
Assessment methods: Giudizio di approvazione
Assessment result: superato/non superato
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
Course syllabus
MODULE 1 - Statistical skills
1. Bibliographic survey
- Consultation of databases
- Analysis and management of the identified literature
2. Introduction to statistics
- Descriptive and inferential statistics
- Concepts of: population, sample, variable
- Qualitative (nominal and ordinal) and quantitative (discrete and continuous) statistical variables
3. Sample definition: data collection and sorting
- Homogeneity of the sample
- Standard error / outliers detection
- Data entry in Excel and calculation of derived variables
- Approval of the data entered within the software
4. Sample analysis
- Minimum / maximum; average / mode / median; differences among averages
- Sample representation (graphs)
- Frequency; percentages
- Standard deviation
- Distribution and quartiles
- Correlation
- Test (Student t, one-way analysis of variance)
- Chi square test
- Probability
MODULE 2 - Computer skills
1. General structures and characteristics of the main spreadsheets and presentation programs
- How to select and apply spreadsheets (MS Excel) and presentation programs (MS PowerPoint)
2. Use of spreadsheets
- Structure of a spreadsheet: management of cells, rows and columns; sheet management. Rational and linear construction of tables
- Basic functions of spreadsheets; how to import and export data
- Application of the main functions (MS Excel): minimum, maximum, se count, median, mode, mean, frequency, quartiles, standard deviation, variance, quadratic deviation, linear forecast, frequency, chi distribution, chi test, correlation, probability, normalize, Student's t distribution and t test
- Criteria for choosing the graphical representations: one, two and three axis diagrams; double ordinate; careful choice of measurement scales
- Pivot tables
3. Use of presentation programs
- The communication of information
- Structure of a representation program (MS PowerPoint): slides management
- How to structure a PowerPoint presentation
- Data and graphics to be included in a presentation; how to import and export
- How to manage movies and audio comments
MODULE 3 - Data management in the winery
1. Geographical, pedo-landscape and climatic framework: resources and methodologies
2. Meteorological course of the year: resources and methodologies
3. Agricultural framework: landscape and agricultural system
4. Winery description: legal and structural aspects
5. Land assets. Land and buildings: maps and description
6. Viticultural plants: genetic resources and type of plant
7. Machinery and equipment
8. Cellar: systems and equipment
9. Vineyard management: techniques and technical means
10. Vinification chain: techniques and technical means
11. Structure of the internship report
1. Bibliographic survey
- Consultation of databases
- Analysis and management of the identified literature
2. Introduction to statistics
- Descriptive and inferential statistics
- Concepts of: population, sample, variable
- Qualitative (nominal and ordinal) and quantitative (discrete and continuous) statistical variables
3. Sample definition: data collection and sorting
- Homogeneity of the sample
- Standard error / outliers detection
- Data entry in Excel and calculation of derived variables
- Approval of the data entered within the software
4. Sample analysis
- Minimum / maximum; average / mode / median; differences among averages
- Sample representation (graphs)
- Frequency; percentages
- Standard deviation
- Distribution and quartiles
- Correlation
- Test (Student t, one-way analysis of variance)
- Chi square test
- Probability
MODULE 2 - Computer skills
1. General structures and characteristics of the main spreadsheets and presentation programs
- How to select and apply spreadsheets (MS Excel) and presentation programs (MS PowerPoint)
2. Use of spreadsheets
- Structure of a spreadsheet: management of cells, rows and columns; sheet management. Rational and linear construction of tables
- Basic functions of spreadsheets; how to import and export data
- Application of the main functions (MS Excel): minimum, maximum, se count, median, mode, mean, frequency, quartiles, standard deviation, variance, quadratic deviation, linear forecast, frequency, chi distribution, chi test, correlation, probability, normalize, Student's t distribution and t test
- Criteria for choosing the graphical representations: one, two and three axis diagrams; double ordinate; careful choice of measurement scales
- Pivot tables
3. Use of presentation programs
- The communication of information
- Structure of a representation program (MS PowerPoint): slides management
- How to structure a PowerPoint presentation
- Data and graphics to be included in a presentation; how to import and export
- How to manage movies and audio comments
MODULE 3 - Data management in the winery
1. Geographical, pedo-landscape and climatic framework: resources and methodologies
2. Meteorological course of the year: resources and methodologies
3. Agricultural framework: landscape and agricultural system
4. Winery description: legal and structural aspects
5. Land assets. Land and buildings: maps and description
6. Viticultural plants: genetic resources and type of plant
7. Machinery and equipment
8. Cellar: systems and equipment
9. Vineyard management: techniques and technical means
10. Vinification chain: techniques and technical means
11. Structure of the internship report
Prerequisites for admission
A basic computer knowledge at the hardware level on the use of the computer is required.
Teaching methods
The 3 modules (statistical skills, computer science skills and data management skills in winery) are developed in serial mode, with the following details.
1) Module: "Statistical Skills": the module begins with a series of classroom lectures introducing the fundamentals of descriptive and inferential statistics. This is followed by practical exercises aimed at applying the concepts covered during the lectures. Particular emphasis is placed on developing students' skills in consulting widely used scientific databases. The teaching methods are designed to provide students with foundational yet practical knowledge of the subject, ensuring its applicability in the subsequent module. All activities are conducted in the classroom.
2) Module: "Computer Science Skills": the teaching activities in this module aim to equip students with proficiency in using the statistical functions of MS Excel, building on the content introduced in the previous module. Specifically, the module begins with an in-depth exploration of Excel's advanced functions, particularly those related to statistical analysis. Subsequent lessons focus on the preparation of PowerPoint presentations, emphasizing both traditional content structuring and the comprehensibility and visual appeal of the materials. The teaching methods aim to enable students to effectively present study findings and research results, with special attention to the final thesis presentation at the end of the three-year degree program. All activities are conducted in the classroom.
3) Data Management Skills in Winery": the module includes lectures, in-depth seminars, in-class and field exercises, and educational visits. Details in the following. Lectures: provide the analytical and theoretical knowledge necessary to understand the key aspects of a winery and its activities. This foundation prepares students to undertake the subsequent institutional internship with maximum awareness and effectiveness. Seminars: designed to stimulate critical thinking and deeper exploration of specific topics. In-class and field exercises: enhance students' ability to analyze practical aspects of data collection relevant to describing a winery business. Practical exercises enable students to apply theoretical knowledge in real-world contexts, both in the classroom and in the field. This teaching approach directly supports the achievement of the expected learning outcomes, particularly in analyzing the multiple descriptors of a winery business and its activities across different territorial contexts, with a focus on the internship period. Field visits and winery tours: offer a real-world context to observe and understand the practical application of classroom knowledge, contributing to the development of practical and applied skills.
1) Module: "Statistical Skills": the module begins with a series of classroom lectures introducing the fundamentals of descriptive and inferential statistics. This is followed by practical exercises aimed at applying the concepts covered during the lectures. Particular emphasis is placed on developing students' skills in consulting widely used scientific databases. The teaching methods are designed to provide students with foundational yet practical knowledge of the subject, ensuring its applicability in the subsequent module. All activities are conducted in the classroom.
2) Module: "Computer Science Skills": the teaching activities in this module aim to equip students with proficiency in using the statistical functions of MS Excel, building on the content introduced in the previous module. Specifically, the module begins with an in-depth exploration of Excel's advanced functions, particularly those related to statistical analysis. Subsequent lessons focus on the preparation of PowerPoint presentations, emphasizing both traditional content structuring and the comprehensibility and visual appeal of the materials. The teaching methods aim to enable students to effectively present study findings and research results, with special attention to the final thesis presentation at the end of the three-year degree program. All activities are conducted in the classroom.
3) Data Management Skills in Winery": the module includes lectures, in-depth seminars, in-class and field exercises, and educational visits. Details in the following. Lectures: provide the analytical and theoretical knowledge necessary to understand the key aspects of a winery and its activities. This foundation prepares students to undertake the subsequent institutional internship with maximum awareness and effectiveness. Seminars: designed to stimulate critical thinking and deeper exploration of specific topics. In-class and field exercises: enhance students' ability to analyze practical aspects of data collection relevant to describing a winery business. Practical exercises enable students to apply theoretical knowledge in real-world contexts, both in the classroom and in the field. This teaching approach directly supports the achievement of the expected learning outcomes, particularly in analyzing the multiple descriptors of a winery business and its activities across different territorial contexts, with a focus on the internship period. Field visits and winery tours: offer a real-world context to observe and understand the practical application of classroom knowledge, contributing to the development of practical and applied skills.
Teaching Resources
For all 3 modules, the reference material are the handouts prepared by the teachers, integrated with several videos and web references. All the material is available in the dedicated section of the Ariel website.
In addition, for the "Statistics skills" module, the following book is recommended: Pelosi M.K, Sandifer M.K., Cerchiello P., Giudici P. "Introduction to Statistics", McGraw-Hill 2nd edition.
In addition, for the "Statistics skills" module, the following book is recommended: Pelosi M.K, Sandifer M.K., Cerchiello P., Giudici P. "Introduction to Statistics", McGraw-Hill 2nd edition.
Assessment methods and Criteria
- Statistical skills module: both during the course and then thanks to dedicated sessions, a test with 24 multiple choice questions and one open-ended question is proposed, this last on a wide-ranging topic inherent to the program. The test must be completed in one hour and its assessment is approved / not approved.
- Computer skills module: the preparation of a Power Point report is required. Starting from statistical data found in public databases (e.g. ISTAT) or provided by Bodies and Associations (preferably in the wine sector), different aspects of the chosen topic are analyzed. The analysis must be conducted with the application of the MS Excel software and must contain statistical aspects shown in the previous module. The presentation setting must follow the classic scheme: a) Introduction; b) materials and methods; c) results and discussion: d) conclusions.
The paper can be prepared and presented individually or by a maximum of two students. The duration of the presentation must not exceed 15 minutes. The test assessment is approved / not approved.
- Data management skills module in a winery: the exam is oral and consists of a verification of the understanding of a practical aspect covered in the program. Its evaluation is approved / not approved
3) Data Management Skills in Winery: students who have attended at least 75% of the module's total hours are eligible to take a simplified oral exam during the final hour of the last lesson. This exam consists of a brief interview focusing on two topics from the syllabus, with an emphasis on a winery that was the subject of a study visit. The evaluation will be based on the clarity and completeness of the responses, and the result, either "approved" or "not approved", will be communicated immediately. In the case of a "not approved" outcome, the student must retake the exam following the standard procedure, shown in the following. The standard exam involves a longer oral interview covering 5 topics from the syllabus. As with the simplified exam, the evaluation will focus on the clarity and completeness of the responses, and the outcome will again be either "approved" or "not approved."
Students with specific learning disabilities (LD) or other disabilities are requested to contact the teachers via email at least 15 days prior to the exam session to agree any compensatory measure. In the email, addressed to the teacher, the relevant University support services must be reoprted in cc: [email protected] (for students with LD) and [email protected] (for students with other disabilities).
- Computer skills module: the preparation of a Power Point report is required. Starting from statistical data found in public databases (e.g. ISTAT) or provided by Bodies and Associations (preferably in the wine sector), different aspects of the chosen topic are analyzed. The analysis must be conducted with the application of the MS Excel software and must contain statistical aspects shown in the previous module. The presentation setting must follow the classic scheme: a) Introduction; b) materials and methods; c) results and discussion: d) conclusions.
The paper can be prepared and presented individually or by a maximum of two students. The duration of the presentation must not exceed 15 minutes. The test assessment is approved / not approved.
- Data management skills module in a winery: the exam is oral and consists of a verification of the understanding of a practical aspect covered in the program. Its evaluation is approved / not approved
3) Data Management Skills in Winery: students who have attended at least 75% of the module's total hours are eligible to take a simplified oral exam during the final hour of the last lesson. This exam consists of a brief interview focusing on two topics from the syllabus, with an emphasis on a winery that was the subject of a study visit. The evaluation will be based on the clarity and completeness of the responses, and the result, either "approved" or "not approved", will be communicated immediately. In the case of a "not approved" outcome, the student must retake the exam following the standard procedure, shown in the following. The standard exam involves a longer oral interview covering 5 topics from the syllabus. As with the simplified exam, the evaluation will focus on the clarity and completeness of the responses, and the outcome will again be either "approved" or "not approved."
Students with specific learning disabilities (LD) or other disabilities are requested to contact the teachers via email at least 15 days prior to the exam session to agree any compensatory measure. In the email, addressed to the teacher, the relevant University support services must be reoprted in cc: [email protected] (for students with LD) and [email protected] (for students with other disabilities).
- University credits: 9
Practicals: 32 hours
Lessons: 56 hours
Lessons: 56 hours
Shifts:
Professor(s)
Reception:
On appointment
Room 3006, via L. Vanvitelli n.32, 3rd floor
Reception:
by appointment only (preferably defined via e-mail)
Dipartimento di Scienze Agrarie e Ambientali - via Celoria, 2 - 20133 Milano