COMPUTER SCIENCE AND STATISTICS FOR ENGINEERING

Degree course: 
Corso di First cycle degree in ENGINEERING FOR WORK AND ENVIRONMENT SAFETY
Academic year when starting the degree: 
2023/2024
Year: 
2
Academic year in which the course will be held: 
2024/2025
Course type: 
Basic compulsory subjects
Language: 
Italian
Credits: 
6
Period: 
Second semester
Standard lectures hours: 
48
Detail of lecture’s hours: 
Lesson (48 hours)
Requirements: 

Analisi Matematica A

Final Examination: 
Orale

The learning assessment is divided into the delivery of 3 homeworks to be done at home and a written test in which you are asked to answer simple questions on theoretical topics and solve one or more simple problems using the tools learned in class including learned informatic tools (ability to use learned software) and relating to the entire program carried out..
The topics covered in the seminars are an integral part of the program and subject to examination.
The delivery of the exercises carried out in the classroom allows to add up to 3 points to the final grade.
To pass the exam, the student must demonstrate adequate theoretical knowledge of all the topics covered by demonstrating mastery of the topics, ability to analyze and solve practical questions using the tools studied, including the ability to use learned software tools.
In the answers the correct use of the tools learned as well as the completeness of the analysis and synthesis in the presentation of the topics also using diagrams will be evaluated.
The exam is passed if all the learning targets are fulfilled (statistic and informatic) with a minimum score of 18 out of 30 (the home essay does not contribute to exceeding the threshold for passing). In case one of the learning targets is insufficient the exam is insufficient.

Assessment: 
Voto Finale

AIM OF THE COURSE
The main objective of the course is to provide the main knowledge so that students acquire the ability to use statistical and information technology tools for the analysis of data and the study of physical phenomena relating to safety as well as the basis for the use of CAD systems for the design and study of systems.
The basis for the calculation of probability and the use of statistical tools for data analysis and the study of phenomena will be taught. Alongside the theoretical part, knowledge will be provided for the use of the main information technology tools for data analysis and process study (spreadsheets, Matlab and statistical software, CAD).
EXPECTED LEARNING OUTCOMES
At the end of the course, the student will be able to:
1. Use the information technology tools learned;
2. Study data and phenomena using appropriate analysis methods
3. Analyze data and phenomena using information technology tools
4. Know how to use statistical analysis, measurements and probability concepts
5. Acquire a precise and adequate technical language to describe the topics addressed;
6. Use of CAD tools

STATISTICS (22h)
• definition of event, statistical sample, population
• sets and operations on sets
• calculation of the number of events
• hints of probability (simple and compound), distributions and characteristic quantities (median, mode, variance)
• Main probability theorems
• Probability distribution and Cumulative distribution function
• Quantiles
• statistical tests (hypothesis test and p-value)
• Measurements (measurand and uncertainty, uncertainty bar, linear and logarithmic scale)
• Linear regression
COMPUTER SCIENCE (22h)
• Use of CAD systems for engineering
• Use of Excel for data analysis
• Use of Matlab for simulation and data analysis, typical instructions of programming languages (if - else, for, while)
• Use of R for statistical analysis
• Data interpolation tools and methods
• Tools for solving differential equations
EXAMPLES (8h)
• Analysis of measurements and comparison of data series
• Drawing with CAD systems and simulation of phenomena

Convenzionale

Frontal teaching with practical lessons in the computer room.
Classroom seminars held by experts.
Classroom exercises with the teacher.

Students can meet with the professor in her office or in teams by previous email appointment (sabrina.copelli@uninsubria.it, elisabetta.sieni@uninsubria.it)

Professors