Unit MEDICAL STATISTICS, COMPUTER SCIENCE AND MATEMATICS

Course
Pharmacy
Study-unit Code
A002507
Location
PERUGIA
Curriculum
In all curricula
Teacher
Massimo Moretti
CFU
9
Course Regulation
Coorte 2021
Offered
2021/22
Type of study-unit
Obbligatorio (Required)
Type of learning activities
Attività formativa integrata

MATHEMATICS

Code 55106206
Location PERUGIA
CFU 3
Teacher Antonio Boccuto
Teachers
  • Antonio Boccuto
  • Antonio Boccuto
Hours
  • 21 ore - Antonio Boccuto
  • 20 ore - Antonio Boccuto
Learning activities Affine/integrativa
Area Attività formative affini o integrative
Academic discipline MAT/05
Type of study-unit Obbligatorio (Required)
Language of instruction ITALIAN
It is possible to do the examination also in English.
Contents The program is divided into four parts:
1) Elements of analytic geometry, trigonometry, inequalities, sets, real
numbers, elementary functions, injective, surjective and bijective
functions. Composite functions Percentuals.
2) Limits, derivatives and study of functions.
3) Integrals and applications to probability and statistics. Definite and
indefinite integral.
Improper integrals.
Gamma function. Distribution function. Probability density.
4) Combinatorics and probability. Conditioned probability. Bayes formula.
Elements of descriptive statistics: mean, median, mode, variance, mean
square error, covariance, correlation coefficient, regression line.
Reference texts Material given by the teacher.
Educational objectives The aim of the course is to introduce, form and illustrate the basic
mathematics to well understand natural phaenomena and several
applications to various branches of sciences, taking into account the
poetry and the art hidden in Mathematics, to arouse the curiosity of the
students. It is required that the student handles fluently the fundamental
tools and have the basic notions of Linear Algebra and Statistics, which
are useful for successive studies in several sciences, in order to
investigate some fundamental aspects of them. It is requested also that
the student is able to work in team, but also in autonomy.
Prerequisites To better understand the topics covered in the course the student should
be familiar with notions like decomposition of simple algebraic
expressions, set theory (union, intersection, complement, difference,
Venn diagram, algebra of sets), resolution of linear and quadratic
equations and inequalities, investigation on polynomials.
Teaching methods The frequence is not officially obligatory, but warmly suggested, AS WELL
AS A DAILY SERIOUS AND RESPONSIBLE STUDY.
The course is split into theoretical lessons and practical lessons, which
will be given by means of a projector and/or a computer, in these latter
several exercises are carried out in class. The course is organized by
means of these kinds of lectures and supplementary didactical activities,
which
include the tutorial service and in which the students are followed
individually by the teacher.
Other information The hours dedicated to exercises are FUNDAMETAL!!!
Learning verification modality The exam consists in a series of tests,
to establish together with the students.
The test is oral, and MAY be preceded by some written tests (NOT NECESSARILY) ONLY IF THE SITUATION RETURNS TO THAT BEFORE COVID. The teacher will ask ALL THE SUBJECTS IN DETAIL, INCLUDED SOME EXERCISES WHICH MUST BE DONE IMMEDIATELY.
Extended program The program is divided into four parts:
1) Elements of analytic geometry, trigonometry, inequalities, sets, real
numbers, elementary functions, injective, surjective and bijective
functions. Percentuals, equivalences.
2) Limits, derivatives and study of functions, and related theorems.
3) Integrals and applications to probability and statistics. Definite and
indefinite integral.
Fundamental theorems. Improper integrals.
Gamma function. Distribution function. Probability density.
4) Combinatorics and probability. Conditioned probability. Bayes formula.
Elements of descriptive statistics: mean, median, mode, variance, mean
square error, quartiles, percentiles, covariance, correlation coefficient,
regression line.The program is divided into four parts:
1) Elements of analytic geometry, trigonometry, inequalities, sets, real
numbers, elementary functions, injective, surjective and bijective
functions. Composite functions Percentuals.
2) Limits, derivatives and study of functions.
3) Integrals and applications to probability and statistics. Definite and
indefinite integral.
Improper integrals.
Gamma function. Distribution function. Probability density.
4) Combinatorics and probability. Conditioned probability. Bayes formula.
Elements of descriptive statistics: mean, median, mode, variance, mean
square error, covariance, correlation coefficient, regression line.

MEDICAL STATISTICS, COMPUTER SCIENCE

Code A002508
Location PERUGIA
CFU 6
Teacher Massimo Moretti
Teachers
  • Massimo Moretti
Hours
  • 42 ore - Massimo Moretti
Learning activities Base
Area Discipline matematiche, fisiche, informatiche e statistiche
Academic discipline MED/01
Type of study-unit Obbligatorio (Required)
Language of instruction Italian.
Contents General principles of statistics and traditional epidemiology.
Risk analysis.
Reference texts Lantieri P.B., Risso D., Ravera G. "Statistica Medica per le Professioni Sanitarie" - McGraw-Hill, 2004.
Educational objectives The learning experiences should help students in achieving attitudes and practices on common techniques used in statistics and epidemiology.
Prerequisites None.
Teaching methods Face-to-face lessons.
Learning verification modality Written (open-ended and closed-ended questions) + oral exam.
Extended program Essentials of Medical Statistics:
Numerical/categorical variables.
Analysis of numerical outcomes: mean/median, standard deviation, standard error.
The normal distribution. Inferential statistics.
Comparison of two means: hypothesis tests and p-values. Student's t-test, ANOVA, Chi-square test.

Epidemiologic Methods:
Epidemiology: definition and scope. Rates of morbidity and mortality. Mortality tables. Population pyramids.
Study design: Observational and experimental epidemiology.
Ecological studies. Cross-sectional studies. Measures of disease frequency: prevalence and incidence.
Analytical epidemiology: cohort studies and case-control studies. Causal and/or noncausal association. Evaluation of relative risk (RR) and odds-ratio (OR); attributable risk.
Experimental epidemiology: preventive trials, randomized controlled trials.
Evidence-based medicine: systematic reviews and meta-analysis.

Risk Analysis:
IARC classification for carcinogenicity.
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