Calculus and Statistics
A.Y. 2022/2023
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
Responsible
Lesson period
First semester
MAT/05 - MATHEMATICAL ANALYSIS - University credits: 6
Practicals: 16 hours
Lessons: 40 hours
Lessons: 40 hours
Professor:
Manicone Francescopaolo
Linea MZ
Lesson period
First semester
The lessons will be held face to face on tuesday from 15.30 to 17.30 and on friday from 9.30 to 12.30, starting from October 2020. A team on Microsoft Teams will be set up for teaching for contacts and receptions and for sharing educational material .
Course syllabus
Real numbers, coordinates on the line and in the plane. Form of a real number.
- Remarkable products. Equations and inequalities.
- Notion of function and its graph. Domain and codomain. Properties of functions: injective; surjective; bijective. Inverse function and compound function.
- Graphs of elementary functions, in particular: lines, powers, absolute value, parabolas, exponentials, logarithms and goniometric functions.
- Translations and symmetries starting from the graph of elementary functions.
- Notion of Limit. Limits of elementary functions. Infinity scale.
- Continuous functions.
- Theorems on continuous functions. Weirstrasse theorem; Theorem of zeroes and Darboux's theorem.
-Points of discontinuity. Asymptotes.
- Notion of derivative in a point and its geometric meaning. Line tangent to the graph of a function at a point.
- Rules of derivation; sum, product, quotient and composition of functions.
- Higher order derivatives.
Theorems on differentiable functions: Rolle, Lagrange and Fermat theorem.
- Application of derivatives to the study of the graph of a function.
-Definition of indefinite integral. Methods of integration.
-Theory of the definite integral. The integral function.
The fundamental theorem of integral calculus.
The mean value theorem.
- Discrete random variables.
- Mean value, variance, standard deviation, standard deviation.
- Double entry tables. Conditional distributions.
- Theoretical frequencies of independence. Contingencies. The normalized chi-square index.
- Linear regression (least squares method).
-Linear correlation.
- Remarkable products. Equations and inequalities.
- Notion of function and its graph. Domain and codomain. Properties of functions: injective; surjective; bijective. Inverse function and compound function.
- Graphs of elementary functions, in particular: lines, powers, absolute value, parabolas, exponentials, logarithms and goniometric functions.
- Translations and symmetries starting from the graph of elementary functions.
- Notion of Limit. Limits of elementary functions. Infinity scale.
- Continuous functions.
- Theorems on continuous functions. Weirstrasse theorem; Theorem of zeroes and Darboux's theorem.
-Points of discontinuity. Asymptotes.
- Notion of derivative in a point and its geometric meaning. Line tangent to the graph of a function at a point.
- Rules of derivation; sum, product, quotient and composition of functions.
- Higher order derivatives.
Theorems on differentiable functions: Rolle, Lagrange and Fermat theorem.
- Application of derivatives to the study of the graph of a function.
-Definition of indefinite integral. Methods of integration.
-Theory of the definite integral. The integral function.
The fundamental theorem of integral calculus.
The mean value theorem.
- Discrete random variables.
- Mean value, variance, standard deviation, standard deviation.
- Double entry tables. Conditional distributions.
- Theoretical frequencies of independence. Contingencies. The normalized chi-square index.
- Linear regression (least squares method).
-Linear correlation.
Prerequisites for admission
Basics of arithmetic and algebra: literal calculation, first and second degree numerical equations in R; first and second degree inequalities in R.
Teaching methods
Frontal lesson in class with multimedia aid
Teaching Resources
Any commercial mathematical analysis text adopted in high school or university level;
handout produced by the teacher and distributed by AD COPIE
Course slides published on the ARIEL website
handout produced by the teacher and distributed by AD COPIE
Course slides published on the ARIEL website
Assessment methods and Criteria
written test: five / six exercises to solve concerning the practical aspects covered in class; a question of theory.
Evaluation expressed in thirtieths.
Evaluation expressed in thirtieths.
MAT/05 - MATHEMATICAL ANALYSIS - University credits: 6
Practicals: 16 hours
Lessons: 40 hours
Lessons: 40 hours
Professor:
Musone Massimiliano
Educational website(s)
Professor(s)