Mathematics and Statistics
A.Y. 2019/2020
Learning objectives
To present the methods, as well as the mathematical and statistical basic tools that should be part of the knowledge base of any graduate with a scientific degree
Expected learning outcomes
By the end of the course, the students will:
- know how to use calculus tools and represent functions;
- understand certain demonstration and representation processes;
- analyze, interpret and reprocess statistical data.
- know how to use calculus tools and represent functions;
- understand certain demonstration and representation processes;
- analyze, interpret and reprocess statistical data.
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
Single session
Lesson period
First semester
Course syllabus
Number sets. Decimal and binary system. Power properties. Algebraic inequalities. Linear function in the plane. Functions and their characteristics. Inverse functions. Composite functions. Power, logarithmic, exponential and trigoniometric functions . Logarithmic and exponential equations and inequalities. Rigid transformations: definition, equations and properties; graph transformations of a function. Absolute value. Limits: definitions and calculation. Continuous functions. Asymptotes. First derivative: definition and geometric meaning. Line tangent to a graph. Computing derivatives. Differentiability and continuity. High-order derivatives . Local and global maxima and minima . Points of inflection . Proof of some important theorems of differential calculus. Study of the graph of a function.
Short history of statistics. Descriptive and inferential statistic. Frequency tables. Graphic rappresentation of data. Means and their use. Variability indexes. Gaussian distribution. Z scores.
Short history of statistics. Descriptive and inferential statistic. Frequency tables. Graphic rappresentation of data. Means and their use. Variability indexes. Gaussian distribution. Z scores.
Prerequisites for admission
Basic knowledge of math at high school level
Teaching methods
In-class lectures, with student collaboration also through the use of information technology. Individual and group exercises.
Teaching Resources
Materials uploaded on the Ariel platform
Assessment methods and Criteria
Written exam, 50 minutes duration, consisting of 8 short exercises which require only to write the final calculation/answer (2 points each), and three open-ended questions (5 point each). Open-ended questions could involve explaining concepts, demonstrating theorems, graphs of functions. The exam score will be out of 30. The grade will take into account the appropriateness of language used.
MAT/01 - MATHEMATICAL LOGIC
MAT/02 - ALGEBRA
MAT/03 - GEOMETRY
MAT/04 - MATHEMATICS EDUCATION AND HISTORY OF MATHEMATICS
MAT/05 - MATHEMATICAL ANALYSIS
MAT/06 - PROBABILITY AND STATISTICS
MAT/07 - MATHEMATICAL PHYSICS
MAT/08 - NUMERICAL ANALYSIS
MAT/09 - OPERATIONS RESEARCH
MAT/02 - ALGEBRA
MAT/03 - GEOMETRY
MAT/04 - MATHEMATICS EDUCATION AND HISTORY OF MATHEMATICS
MAT/05 - MATHEMATICAL ANALYSIS
MAT/06 - PROBABILITY AND STATISTICS
MAT/07 - MATHEMATICAL PHYSICS
MAT/08 - NUMERICAL ANALYSIS
MAT/09 - OPERATIONS RESEARCH
Practicals: 16 hours
Lessons: 72 hours
Lessons: 72 hours
Professor:
Degavi Emilia Maria
Shifts:
Matematica
Professor:
Degavi Emilia MariaStatistica
Professor:
Degavi Emilia Maria