Mathematics and foundations of computer science and statistics
There are no prerequisites.
A pre-course on the basic topics is provided before the beginning of the Math Course.
The exam consists of two parts:
1. WRITTEN EXAMINATION:
a. Part A Exercises on the basic topics covered in the pre-course (this part is mandatory only for students who have not passed the final test of the pre-course).
b. Part B (to access to the Part B you must pass the part A with evaluation higher than or equal to 18/30):
4 exercises (1 exercise with a complete study of function, 1 exercise on vectors and matrices or graphs deductible or continuity and differentiability or limits or theorems’ application, 1 exercise on univariate and bivariate statistics or statistical distributions or probability, 1 exercise on inferential statistics or statistical distributions or probability or statistical tests)
2. Admission to oral examination:
• grade of the written test <12/30: non-admission to the oral exam
• grade of the written test from 12/30 to 17/30: conditional admission to oral exam
• grade of the written test from 18/30 to 20/30: It is proposed to confirm this grade
• grade of the written test from 21/30 to 30/30: admission at the oral exam
3. ORAL EXAM
• correction and discussion of written examination
• resolution of exercises similar to those presented in the course
• definitions, statements of theorems, demonstrations
• examples in the applied sciences presented in class and on the textbook
• knowledge and use of the software Graph (for function graphs) and the spreadsheet (for statistics)
The final grade will be determined as the average of written and oral grade
NOTE: You may use only statistical tables and non-programmable scientific calculator during the examination.
SUBJECT GOALS
Introduction and training goals
The course objective is to provide the necessary basis for the analytical understanding of basic aspects of scientific phenomena and in particular biological, through the acquisition of the basic methods of mathematical analysis, linear algebra, the theory of probability and statistics.
LEARNING OUTCOMES
Knowledge and understanding (Knowledge and know)
At the end of the course students will possess the knowledge necessary for a correct interpretation of the biological experimental data and a correct understanding of the performance of the biological phenomena.
Applying knowledge and understanding (Skills and know how)
At the end of the course students will be able to use the mathematical-statistical instrument to modeling biological phenomena and to understand at the molecular level their thermodynamic, kinetic, electromagnetic aspects etc. and biological processes such as enzymatic catalysis and the transmission of electrochemical signals.
Univariate Descriptive Statistics. Bivariate Descriptive Statistics. Linear regressions. Basics of computer science with use of mathematical applications and spreadsheets. Basic elements of probability theory. Basic elements of linear algebra: vectors and matrices. Limits and continuity. Differential and integral calculus. Discrete and continuous distributions. Elements of inferential statistics and statistical tests.
The recommended text is Benedetto-Degli Esposti-Maffei - "Matematica per le scienze della vita" - Casa Editrice Ambrosiana. Slides of the lessons and additional material are available in the e-learning platform
Front lessons. There are also 36 hours of classroom training with specific exercises for the preparation of the final assessment