Learning objectives
The course has as its objective the knowledge of statistical indices and the ability to understand the output information from a table of data. At the end of the course the student will be able to identify and study the Bernoulli and Gauss distributions.
Prerequisites
Operations in the set of real numbers. Logarithmic and exponential calculus.
Course unit content
Lectures on Statistics and Probability applied to the biomedical sciences.
First lessons cover topics of general interest related to the foundations of Mathematics and Logic such as operations in numerical sets and predicate calculus.
The second part regards the discussion of the fundamental contents of Statistics: data collection, averages and dispersion indicators. The third part is devoted to combinatorics, probability calculus, Gauss and Bernoulli distributions.
Full programme
Elementary theory of sets - Elements of Logic - Numerical sets, operations and properties - Applications: proportions and percentages - Applications: equivalences - Floating point representation of real numbers - Operations in scientific notation - Truncation and rounding approximations - Significant digits - Outline of functions - Real functions of real variable - Qualitative properties - Polynomial, exponential and logarithmic functions -
Elements of descriptive statistics: data collection, classification and graphical representation - Frequency distributions - Avarages, mode, median, squared error,
variance, standard deviation, index of variation - Gauss distribution - Two characters distribution - Combinatorics - Events and discrete probability calculus - Elements of probability theory - Bernoulli distribution.
Bibliography
C. Sbordone, F. Sbordone: “Matematica per le Scienze della Vita”, EdiSES, (2014)
M. Abate: “Matematica e Statistica, Le basi per le scienze della vita”, McGraw-Hill, (2009)
V. Villani: “Matematica per le discipline bio-mediche”, Quarta edizione, McGraw-Hill, (2007)
A.Aimi: "Appunti di Matematica di base applicata alle scienze biomediche", (obtained from the slides used during lectures, a.y. 2014/15)
Teaching methods
During lectures, pdf slides will be screened on the topics of the course, which will be always supported by examples and classroom exercises performed by the teacher or by the students under the supervision of the teacher. Their purpose is to provide the opportunity for each student to be able to measure himself in independently obtaining the solutions to problems presented in theoretical form during lectures.
Assessment methods and criteria
• Written final examination
• Pass mark: 18/30; Maximum score: 33/30 ("cum laude")
• Since it is an integrated teaching together with Physics and Computer Science, the final score will be the arithmetic average of the three marks, which have to be anyway all equal or greater than 18/30.
Other information
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2030 agenda goals for sustainable development
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