MATHEMATICS AND STATISTICS
- Overview
- Assessment methods
- Learning objectives
- Contents
- Delivery method
- Teaching methods
- Contacts/Info
The only prerequisite is the basic knowledge of mathematics acquired during high school, which will be reviewed anyways at the beginning of the lecture.
Written exam consisting of 20 multiple-choice questions.
There is the possibility to take a supplementary oral exam, which is optional for those who obtained a grade of 18 or higher in the written part, and mandatory for those who have obtained a mark between 15 and 17 included.
After the oral exam, the committee can increase or decrease the written exam grade. A decrease in the grade can result in the failure of a candidate, even if they have obtained a grade of 18 or higher in the written exam.
The primary goal of the course is to provide students with those foundational knowledge of mathematis and statistics which are essential for the specialized subjects they will engage with throughout their degree program.
At the end of the lecture, students will be able to:
- understand the basic concepts of mathematical analysis;
- understand the basic concepts of mathematical statistics;
- apply these concepts to situations of interest in the areas which are relevant for their degree.
MATHEMATICS
1) Review of basic mathematics: number sets, data representation, approximation of numerical data. Powers, roots, and logarithms. Equations and inequalities. Basic trigonometry.
2) Linear systems of equations: the Gauss algorithm.
3) Mathematics and infinity: induction, sequences and limits
4) Elementary functions: graphs, continuity, growth and decrease. Elements of calculus: geometric meaning of derivatives, computation rules, and applications to study of functions.
5) Elements of integral calculus: geometric meaning of the definite integral, computation of primitives, and applications to computation of areas.
6) Differential equations and basic notions of dynamical systems.
STATISTICS
1) Fundamentals of Probability: Probability measures, continuous and discrete random variables.
2) Descriptive Statistics: Mean, mode, median, and variance of a sample. Graphical interpretation of data.
3) Inferential Statistics: t-tests and confidence intervals.
4) Univariate Linear Regression
Theoretical lectures where the fundamental concepts of the course will be presented. These lectures will be supported by slides, which will subsequently be provided to the students.
Practical lessons where problems will be solved using the concepts explained during the theoretical lectures.
The course program may be changed or expanded during the year.
For information on the course you may contact the instructors at giovanni.bazzoni@uninsubria.it or da.bignamini@uninsubria.it