The main objective of the course is to guide the student to acquire functional mathematical content and skills in order to master the concepts of mathematical analysis, probability theory, and statistics, useful for learning of the other disciplines of the course of study. Another objective will be to motivate students to study by avoiding during the lessons the treatment of the topics excessively abstract, involving them in the application of mathematics and guiding them to acquire the awareness that the scientific disciplines, often studied as independent, are actually interconnected.
Course Prerequisites
Being an exam of the first year there are no specific prerequisites different from those required for admission to the degree program.
Teaching Methods
Lectures, activity by means of the University's Moodle platform, learning monitoring activity discussed and corrected with the students. Use of the free software Geogebra https://www.geogebra.org/download. Use of the Excel spreadsheet. Although Excel is not a software specifically intended for statistics, it contains many functions and tools that allow performing statistical analyzes and calculations, it is a very popular software and is suitable for immediate use for short-term activities.
Assessment Methods
The exam consists of a 90 minutes written examination (four/five exercises concerning the contents discussed and tested during the course). For each exercise, the maximum expected score will be indicated (from a minimum of 3 to a maximum of 12 points, based on the difficulty of the assigned exercise). To pass the exam it is necessary to acquire a minimum score of 18. Praise is obtained with a score higher than 30.
Contents
Mathematical Models in Sciences; Linear Algebra; Definition and properties of real functions, notable functions, piecewise functions and graphs; The concept of limit of a real function, property of limits, calculation of limits and indeterminate forms; Study of the continuity of functions, points of discontinuity, statement of the theorems of continuous functions; Derivative of a function in a point; Derivative and linear approximation; Derivative and antiderivative; Derivative and monotonicity; derivative and convexity; Graphs of functions and their transformations; Definite and indefinite integral; Fundamental Theorem of Integral Calculus; Notions of computer science for the construction of simple graphical representations; Descriptive statistics; Probability calculus; Probability distributions; Inferential statistics.
