INFORMATICA CON ELEMENTI DI MATEMATICA E STATISTICA G - O
Academic Year 2023/2024 - Teacher: GIULIA RUSSOExpected Learning Outcomes
Course Structure
Through lessons and practical sessions at the end of each learning unit (when planned).
If the lessons are given in a mixed or remote way, the necessary changes with respect to what was previously stated may be introduced, in order to meet the program envisaged and reported in the syllabus.
To guarantee equal opportunities and in compliance with the laws in force, interested students can ask for a personal interview in order to plan any compensatory and / or dispensatory measures, based on the didactic objectives and specific needs.
It is also possible to contact the referent teacher CInAP (Center for Active and Participated Integration - Services for Disabilities and / or SLD) of our Department, Prof. Teresa Musumeci.
Required Prerequisites
Attendance of Lessons
Detailed Course Content
Elementary functions: power functions and n-th roots, exponential functions, and logarithmic functions: definitions, properties, graphs, applications. The use of exponentials and logarithms in life sciences: models for the evolution of a population, such as that of the bacteria in a culture or the cells in a tissue of an organism. Functions of a real variable: notes on the domain of definition, increase, decrease, maximum and minimum (absolute), composition of elementary functions and their graph. Limits: definitions, properties, calculation rules, order of infinity and infinitesimal, graphical aspects, oblique asymptotes. Derivatives. Integrals: definition, properties, area calculation, approximation using the trapezoid method. Using AI tools for mathematics.
Statistics
Notes and principles of descriptive statistics. Multivariate analysis. Bivariate analysis. Biostatistics. Frequency measures. Risk measures. Distributions (Normal, Gaussian). Central limit theorem. Confidence intervals. Hypothesis testing. Significance.
Computer Science
Fundamental concepts of Information Theory; General concepts: Hardware, Software; Information Technology; Types of computers; Main components of a PC; Computer performance. Hardware: Central Processing Unit; Memory; Input peripherals; Output peripherals; Input/output peripherals; Memory devices. Software: Types of software; System software; Application software; Graphical User Interface; System development. Data mining. Data computerization. Systems for database management. Introduction to computer networks.
Applications
Examples of mathematical/statistical/computer applications in the field of Life Sciences and Drug Discovery.
Textbook Information
Teacher's notes.
Learning Assessment
Learning Assessment Procedures
By written test and oral test.
Verification of learning can also be carried out electronically, should the conditions require it.
Examples of frequently asked questions and / or exercises
1 Let f: A → B, it is called Bijective if: A) the function is Injective. B) f(A) = B. C) the function is Injective and Surjective. D) ∀x', x''∈A, x'≠x''⇒f(x')≠f(x''
2 What is the main characteristic of the Gaussian distribution (or normal distribution)? A) It is a distribution that exhibits bilateral symmetry around its mean value. B) It is a distribution that takes only discrete values. C) It is a distribution that has neither a defined mean nor standard deviation. D) It is a distribution that describes natural phenomena with a rectangular-shaped curve.
3 Mark the True answer. Seek time measures: A) The time it takes for the read/write head to move radially to reach the desired track. B) The time it takes for the desired sector to pass under the read/write head. C) The actual reading time. D) the system startup speed.