Calculus and Statistics
A.Y. 2020/2021
Learning objectives
The course intends to give both the basic concepts of the theory of univariate functions and the basic concepts.
Expected learning outcomes
At the end of the course, students should be able to:
· use real valued functions and Calculus tools to describe easy models;
· handle basic tools in both Statistics and Probability.
· use real valued functions and Calculus tools to describe easy models;
· handle basic tools in both Statistics and Probability.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Linea AL
Lesson period
First semester
The course programme is carried out in presence, asynchronous and synchronous mode through the Teams platform. The disciplinary contents have not undergone significant variations for the pandemic. The students who follow remotely have at their disposal the software presentation carried out in class by the teacher. Appeals will be made in attendance in compliance with anti-covid measures. In the event of a new health emergency, the course will return to full-distance teaching and, if necessary, the appeals will also be made in the event of a new health emergency. Appeals from written mode with multiple-answer questions and problems to be carried out, could switch to oral mode remotely.
Course syllabus
Elements of calculus: sets, number sets, numerical sequences, functions, limits, asymptotic behaviour of Taylor and Mac Lauren's functions and developments, differential calculus in one variable, analysis of a function, integral calculus in one variable. 2. Elements of Statistics: Data and sampling. Graphic presentations. Measures of location: arithmetic mean, geometric mean, median, mode. Measures of dispersion: quartiles, interquartile range, variance and standard deviation. Normal distribution. t-Student. Coefficient of correlation and linear regression line. Iphotesis test
Prerequisites for admission
Knowledge and skill in the following arguments: equations and inequalities of first and second degrees; the equation of a line; trigonometric functions and main identities; properties of powers and logarithms.
Teaching methods
Frontal lessons using multimedia devices. Exercises
Teaching Resources
Handouts provided by the teacher
Assessment methods and Criteria
The general learning outcome is to develop the students' abstract thought, to provide them with basic mathematical concepts, tools and rigorous language, together with problem solving abilities and the capacity to read and understand simple mathematical texts. To this purpose, the methods of calculus will be illustrated and applied to the analysis of real valued functions in one variable. The matrix methods for solving systems of linear equations will be presented, as well as the basic methods of descriptive statistics in the context of life sciences. In this way the students will become skillful at differential and integral calculus, and statistical data analysis.
Examination appeals are in written form, consisting of multiple-choice questions and problems to be explicitly addressed
Examination appeals are in written form, consisting of multiple-choice questions and problems to be explicitly addressed
MAT/05 - MATHEMATICAL ANALYSIS - University credits: 6
Practicals: 16 hours
Lessons: 40 hours
Lessons: 40 hours
Professor:
Bertini Stefano
Linea MZ
Lesson period
First semester
the lessons will be carried out through the Teams platform
Course syllabus
Real number set, real functions , limits and continuity, differential calculus, integral calculus, probability, elements of statistic
Prerequisites for admission
knowledge and skills : algebric equations and inequalities, goniometric equations and inequalities , exponential and logarithmic equations and inequalities. Knowledge of basic function graphs.
Teaching methods
Frontal Lessons and exercises to acquire skills
Teaching Resources
handouts provided by the teacher
Assessment methods and Criteria
the exam appeals are in written mode, which evaluates the acquired skills.
MAT/05 - MATHEMATICAL ANALYSIS - University credits: 6
Practicals: 16 hours
Lessons: 40 hours
Lessons: 40 hours
Professor:
Trentin Cristina