Unit MEDICAL STATISTICS, COMPUTER SCIENCE AND MATEMATICS
 Course
 Pharmacy
 Studyunit Code
 A002507
 Location
 PERUGIA
 Curriculum
 In all curricula
 Teacher
 Massimo Moretti
 CFU
 9
 Course Regulation
 Coorte 2021
 Offered
 2021/22
 Type of studyunit
 Obbligatorio (Required)
 Type of learning activities
 Attività formativa integrata
MATHEMATICS
Code  55106206 

Location  PERUGIA 
CFU  3 
Teacher  Antonio Boccuto 
Teachers 

Hours 

Learning activities  Affine/integrativa 
Area  Attività formative affini o integrative 
Academic discipline  MAT/05 
Type of studyunit  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 

Hours 

Learning activities  Base 
Area  Discipline matematiche, fisiche, informatiche e statistiche 
Academic discipline  MED/01 
Type of studyunit  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"  McGrawHill, 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  Facetoface lessons. 
Learning verification modality  Written (openended and closedended 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 pvalues. Student's ttest, ANOVA, Chisquare test. Epidemiologic Methods: Epidemiology: definition and scope. Rates of morbidity and mortality. Mortality tables. Population pyramids. Study design: Observational and experimental epidemiology. Ecological studies. Crosssectional studies. Measures of disease frequency: prevalence and incidence. Analytical epidemiology: cohort studies and casecontrol studies. Causal and/or noncausal association. Evaluation of relative risk (RR) and oddsratio (OR); attributable risk. Experimental epidemiology: preventive trials, randomized controlled trials. Evidencebased medicine: systematic reviews and metaanalysis. Risk Analysis: IARC classification for carcinogenicity. 