CALCULUS 1 (UNIT 2)
cod. 1004541

Academic year 2024/25
1° year of course - Second semester
Professor
Paolo BARONI
Academic discipline
Analisi matematica (MAT/05)
Field
Formazione matematica di base
Type of training activity
Basic
56 hours
of face-to-face activities
6 credits
hub: PARMA
course unit
in ITALIAN

Integrated course unit module: CALCULUS 1

Learning objectives

At the end of the course, the student must have acquired the basic knowledge and skills of integro-differential calculus for functions of one real variable; he must also be able to understand how these can be applied to solve concrete problems and to handle them easily also in relation to other areas of mathematics. In particular, the student should:

1) be familiar with the concept of convex function, also in relation to the level of regularity of the function itself; have a solid knowledge of the Riemann integration theory (possibly over unbounded intervals and for unbounded functions) and understand how to apply it to the calculation of integrals. Recognize the various convergence criteria for numeric series and include the generalized integral relation. Know the concept of
uniform continuity and its consequences (Knowledge and understanding)

2) apply the theoretical knowledge acquired to the resolution of even complex concrete problems. Understand its applicability to other areas of mathematics (Applying knowledge and understanding)

3) evaluate the consistency and accuracy of the results obtained; analyse the appropriate remedial strategies for solving exercises, relying on the collection of tools they believe to possess (Making judgments)

4) use a formally correct language allowing to communicate clearly, accurately and concisely the content of the program. Frontal lessons and direct comparisons with the teacher will encourage the student to acquire a specific and appropriate scientific vocabulary (Communication skills)

5) deepen their knowledge, starting from the basics provided in the course, in order to be able to appropriately and effectively manage the use of further analytical tools and concepts, both in subsequent courses and in individual study (Learning skills)

6) be able to continue the studies in Mathematics and in other scientific disciplines

7) have a flexible mind that allows her/him to easily handle new challenges and problems, both autonomously and in collaboration, and to acquire new knowledge and information from the available sources

Prerequisites

Course unit content


Convexity, qualitative behavior of differentiable functions, and integral calculus for functions of one variable. Series.

Full programme

Monotonicity: relationship between derivative sign and monotonicity, necessary and sufficient conditions for local maxima/minima, second and k-th order criterion. Continuity of monotone functions.
Convexity: convex sets and functions, monotonicity of incremental ratios, relation between convexity, first derivative and sign of the second derivative. Tangent lines and half-lines

Integrals: partitions of an interval; Riemann sums; Riemann integral; integrability of monotone functions and of continuous functions; integral mean; fundamental theorem of integral calculus; primitives; integration by parts; integration by substitution; integration of rational functions.

Series: Convergent, divergent and undetermined series; series with positive terms, comparison, ratio and root tests; absolute convergence, Leibnitz criterion; esamples: geometric series, telescopic series, generalized harmonic series, alternating harmonic series.

Improper integrals: definition for bounded and unbounded intervals, convergence of the integral, absolute convergence, comparison tests. Integral test for positive valued series.

Complements: Uniform continuity, liminf and limpsup of sequences (and functions), Heine-Borel theorem.

Bibliography

E. Acerbi, G. Buttazzo: Primo corso di Analisi Matematica, Universitas Ed. Parma, 2023.

D. Addona, B. Gariboldi, L. Lorenzi: AM1 - Analisi Matematica 1, Ed. Esculapio, 2022.


Exercises:
D. Addona, B. Gariboldi, L. Lorenzi: AM1 - Analisi Matematica 1 - Esercizi, Ed. Esculapio, 2023.

S. Salsa, A. Squellati: Esercizi di Analisi matematica 1, Ed. Zanichelli, 2023.

Teaching methods

The course includes 5 hours of frontal teaching per week. Lesson will be traditionally held at the blackboard and the topics will be presented rigorously. A direct interaction with students will be encouraged, also in order to highlight any previous gap on the topics dealt with and to promptly attempt to retrieve them. Weekly, a few hours will be devoted to exercises. This will allow to show to the students the applications of the theoretical results and to help them to understand more deeply the theory. Weekly, as part of the individual study, a file will be uploaded to the elly portal. The file will include various exercises to be solved and simple demonstrations, omitted in class, to be completed. Exercise hours will be devoted to the exhaustive resolution of exercises from the previous weeks, considered significant or requested by the students.

Assessment methods and criteria

The evaluation is done in two phases. The first consists in evaluating a written test where the student must solve exercises without the help of books and notes. The first part is successful if the student reaches a score non inferior to 18; the maximum score is 30. For students who have underwent the partial written test scheduled in the first Unit, the written test will just focus on the program of the second Unit and the vote of this will average with those of the first two partial tests. For all the other students, it will cover the whole program of the two Units. Exceeding the written test allows the student to take the oral exam, which will concern the whole program of the course and will mainly focus on theoretical aspects (definitions, theorems, proofs). The student will have to show knowledge and appropriate understanding of the program using a correct mathematical formalism and owing a proper language. The final vote will be given by a weighted average of the two votes. The purpose of this type of assessment is to try to reliably evaluate the level
of achievement of learning outcomes expected above, in particular points 1) to 4).

Other information

2030 agenda goals for sustainable development

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Contacts

Toll-free number

800 904 084

Student registry office

E. segreteria.scienze@unipr.it
T. +39 0521 905116

Quality assurance office

Education manager
dott.ssa Giulia Bonamartini

T. +39 0521 906968
E. servizio smfi.didattica@unipr.it
E. del manager giulia.bonamartini@unipr.it

President of the degree course

Prof. Luca Lorenzi
E. luca.lorenzi@unipr.it

Faculty advisor

Prof. Luca Lorenzi
E. luca.lorenzi@unipr.it

Career guidance delegate

Prof. Francesco Morandin
E. francesco.morandin@unipr.it

Tutor Professors

Prof. Emilio Acerbi
E. emilio.acerbi@unipr.it

Prof. Marino Belloni
E. marino.belloni@unipr.it

Prof.ssa Maria Groppi
E. maria.groppi@unipr.it

Prof.ssa Chiara Guardasoni
E. chiara.guardasoni@unipr.it

Prof. Luca Lorenzi
E. luca.lorenzi@unipr.it

Prof. Costantino Medori
E. costantino.medori@unipr.it

Prof. Adriano Tomassini
E. adriano.tomassini@unipr.it

Erasmus delegates

Prof.ssa Fiorenza Morini
E. fiorenza.morini@unipr.it

Quality assurance manager

Prof.ssa Maria Groppi
E. maria.groppi@unipr.it

Tutor students

Dott. Matteo Mezzadri
E. matteo.mezzadri@studenti.unipr.it