Fabrizio BARONE | MEDICAL STATISTICS AND INFORMATICS

cod. 1060100004

MEDICAL STATISTICS AND INFORMATICS

	1060100004
	DIPARTIMENTO DI MEDICINA, CHIRURGIA E ODONTOIATRIA "SCUOLA MEDICA SALERNITANA"
	EQF7
	MEDICINE AND SURGERY
	2016/2017

PERCORSO COMUNE

	OBBLIGATORIO
	YEAR OF COURSE 1
	YEAR OF DIDACTIC SYSTEM 2016
	SECONDO SEMESTRE

TEACHING UNITS

	SSD	CFU	HOURS	ACTIVITY	TYPE OF ACTIVITY
1	STATISTICA MEDICA E INFORMATICA - MOD STATISTICA MEDICA
	MED/01	4	48	LESSONS	COMPULSORY SUBJECTS, CHARACTERISTIC OF THE CLASS
2	STATISTICA MEDICA E INFORMATICA - MOD INFORMATICA
	ING-INF/06	2	24	LESSONS	BASIC COMPULSORY SUBJECTS

PROFESSORS

	FABRIZIO BARONE1 T Curriculum
	FABRIZIO ESPOSITO2 Curriculum

	Objectives
	THE STUDENT WILL ACQUIRE KNOWLEDGE OF THE MAIN ISSUES OF MEDICAL STATISTICS AND INFORMATICS OF INTEREST TO THE DEGREE COURSE. IN PARTICULAR, HE WILL ACQUIRE KNOWLEDGE OF THE MAIN MODELS AND THEOREMS OF MEDICAL STATISTICS, IN CONNECTION WITH THE ASSUMPTIONS ON WHICH THESE MODELS ARE BASED, CRITICALLY UNDERSTANDING ALSO LIMITS OF VALIDITY AND APPLICABILITY IN REAL CONTEXTS (KNOWLEDGE AND UNDERSTANDING). THE STUDENT WILL BE ABLE TO SUCCESSFULLY APPLY THE MODELS AND THEOREMS OF MEDICAL STATISTICS AND INFORMATICS TO QUALITATIVE AND QUANTITATIVE DESCRIPTION OF REAL CASES ALSO, AND ESPECIALLY, IN INTERDISCIPLINARY CONTEXTS OF INTEREST TO THE DEGREE COURSE, BY TESTING HYPOTHESES AND CONDITIONS ON WHICH THESE MODELS AND THEOREMS ARE BASED. THE STUDENT WILL ALSO BE ABLE TO EVALUATE THE QUALITY OF THE EXPECTED RESULTS BOTH IN RELATION TO THE INTRINSIC APPROXIMATIONS OF THE MODELS AND THEOREMS ADOPTED AND IN RELATION TO THE MEASUREMENT ERRORS (APPLIED KNOWLEDGE AND UNDERSTANDING). THE STUDENT WILL BE ABLE TO INTEGRATE THE NECESSARY KNOWLEDGE AND MANAGE THE COMPLEXITY OF THE INFORMATION IN THE ACQUISITION AND APPLICATION OF THE KNOWLEDGE OF MEDICAL STATISTICS AND INFORMATICS, TO FORMULATE JUDGMENTS AND ASSUMPTIONS OF WORK, ALSO ON THE BASIS OF INCOMPLETE OR LIMITED INFORMATION, AND ON THE EFFECTS AND RESPONSIBILITIES RELATED TO THE PRACTICAL APPLICATION OF THE KNOWLEDGE (INDEPENDENT JUDGMENT). THE STUDENT WILL ACQUIRE THE ABILITY TO PRESENT TOPICS COVERED IN THE COURSE OF MEDICAL STATISTICS AND INFORMATICS WITH PROPERTIES AND SIMPLICITY OF LANGUAGE, AIMED ALSO TO A CLEAR AND EFFECTIVE TRANSMISSION OF CONTENTS AND RESULTS IN INTERDISCIPLINARY CONTEXTS, IN PRESENCE OF INTERLOCUTORS WHO ARE NOT EXPERTS IN THE FIELD (COMMUNICATION). THE STUDENT WILL ACQUIRE SKILLS ALLOWING HIM TO EXPANDING AND DEEPENING THE THEMES OF MEDICAL STATISTICS AND INFORMATICS AND ITS INTERDISCIPLINARY APPLICATIONS IN AN AUTONOMOUS WAY (LEARNING SKILLS).

THE STUDENT WILL ACQUIRE KNOWLEDGE OF THE MAIN ISSUES OF MEDICAL STATISTICS AND INFORMATICS OF INTEREST TO THE DEGREE COURSE. IN PARTICULAR, HE WILL ACQUIRE KNOWLEDGE OF THE MAIN MODELS AND THEOREMS OF MEDICAL STATISTICS, IN CONNECTION WITH THE ASSUMPTIONS ON WHICH THESE MODELS ARE BASED, CRITICALLY UNDERSTANDING ALSO LIMITS OF VALIDITY AND APPLICABILITY IN REAL CONTEXTS (KNOWLEDGE AND UNDERSTANDING).

THE STUDENT WILL BE ABLE TO SUCCESSFULLY APPLY THE MODELS AND THEOREMS OF MEDICAL STATISTICS AND INFORMATICS TO QUALITATIVE AND QUANTITATIVE DESCRIPTION OF REAL CASES ALSO, AND ESPECIALLY, IN INTERDISCIPLINARY CONTEXTS OF INTEREST TO THE DEGREE COURSE, BY TESTING HYPOTHESES AND CONDITIONS ON WHICH THESE MODELS AND THEOREMS ARE BASED. THE STUDENT WILL ALSO BE ABLE TO EVALUATE THE QUALITY OF THE EXPECTED RESULTS BOTH IN RELATION TO THE INTRINSIC APPROXIMATIONS OF THE MODELS AND THEOREMS ADOPTED AND IN RELATION TO THE MEASUREMENT ERRORS (APPLIED KNOWLEDGE AND UNDERSTANDING).

THE STUDENT WILL BE ABLE TO INTEGRATE THE NECESSARY KNOWLEDGE AND MANAGE THE COMPLEXITY OF THE INFORMATION IN THE ACQUISITION AND APPLICATION OF THE KNOWLEDGE OF MEDICAL STATISTICS AND INFORMATICS, TO FORMULATE JUDGMENTS AND ASSUMPTIONS OF WORK, ALSO ON THE BASIS OF INCOMPLETE OR LIMITED INFORMATION, AND ON THE EFFECTS AND RESPONSIBILITIES RELATED TO THE PRACTICAL APPLICATION OF THE KNOWLEDGE (INDEPENDENT JUDGMENT).

THE STUDENT WILL ACQUIRE THE ABILITY TO PRESENT TOPICS COVERED IN THE COURSE OF MEDICAL STATISTICS AND INFORMATICS WITH PROPERTIES AND SIMPLICITY OF LANGUAGE, AIMED ALSO TO A CLEAR AND EFFECTIVE TRANSMISSION OF CONTENTS AND RESULTS IN INTERDISCIPLINARY CONTEXTS, IN PRESENCE OF INTERLOCUTORS WHO ARE NOT EXPERTS IN THE FIELD (COMMUNICATION).

THE STUDENT WILL ACQUIRE SKILLS ALLOWING HIM TO EXPANDING AND DEEPENING THE THEMES OF MEDICAL STATISTICS AND INFORMATICS AND ITS INTERDISCIPLINARY APPLICATIONS IN AN AUTONOMOUS WAY (LEARNING SKILLS).

	Prerequisites
	BASIC KNOWLEDGE OF MATHEMATICS AND INFORMATICS.

	Contents
	TEACHING UNIT: MEDICAL STATISTICS PROBABILITY: CONDITIONAL AND COMPOSED PROBABILITY; COMBINATORIAL ANALYSIS; LINK BETWEEN A PRIORI PROBABILITY AND RELATIVE FREQUENCY. DISTRIBUTIONS: DISTRIBUTIONS AND FREQUENCIES; INDICES OF THE DISTRIBUTION; MEASURES OF DISPERSION; CONTINUOUS PROBABILITY DISTRIBUTIONS; DISCRETE PROBABILITY DISTRIBUTIONS; DISTRIBUTION T OF STUDENT; 2; DISTRIBUTION F OF FISCHER; DEGREES OF FREEDOM; INTRODUCTION TO SIMULATION TECHNIQUES OF EXPERIMENTS. STATISTICAL INFERENCE: THEORY OF THE SAMPLES; ESTIMATION THEORY; THEORY OF DECISIONS; THE 2 TEST; ANALYSIS OF THE VARIANCE; THE FISHER TEST FOR THE VARIANCES; THE T TEST OF STUDENT; THE MC NEMAR TEST. INTERPOLATION AND LEAST SQUARES: INTERPOLATION; EXTRAPOLATION; LEAST SQUARES; OPERATIONAL REQUIREMENTS FOR THE METHOD OF LEAST SQUARES; NUMERICAL EXAMPLES; TIME SERIES. THEORY OF ERRORS: MEASUREMENT ERRORS; SYSTEMATIC ERRORS; ACCIDENTAL ERRORS; INDIRECT MEASUREMENTS; ERROR PROPAGATION. APPLICATIONS: APPLICATIONS OF THE ABOVE TOPICS TO MEDICINE. TEACHING UNIT: INFORMATICS COMPUTER SCIENCE (BASICS AND DEFINITIONS AND): ALGORITHMS, DATA, CODING, PROGRAMMING LANGUAGES, DATABASES, DIGITAL SIGNALS AND IMAGES. HARDWARE & SOFTWARE: COMPUTER TYPES, COMPUTER ARCHITECTURE, OPERATING SYSTEM AND BASE SOFTWARE. APPLICATIONS AND DOCUMENTS OF COMMON USE: BASIC AND ADVANCED FUNCTIONS OF THE SPREADSHEET, USE THE SPREADSHEET FOR DESCRIPTIVE AND INFERENTIAL STATISTICS AND FOR DATA ANALYSIS. COMPUTER NETWORKS: ARCHITECTURES AND COMMUNICATION PROTOCOLS, INTERNET AND E-MAIL, SEARCH ENGINES. INFORMATION SYSTEMS: DATABASES AND BIBLIOGRAPHIC SEARCHES IN BIOMEDICINE.

Contents

TEACHING UNIT: MEDICAL STATISTICS

PROBABILITY: CONDITIONAL AND COMPOSED PROBABILITY; COMBINATORIAL ANALYSIS; LINK BETWEEN A PRIORI PROBABILITY AND RELATIVE FREQUENCY.

DISTRIBUTIONS: DISTRIBUTIONS AND FREQUENCIES; INDICES OF THE DISTRIBUTION; MEASURES OF DISPERSION; CONTINUOUS PROBABILITY DISTRIBUTIONS; DISCRETE PROBABILITY DISTRIBUTIONS; DISTRIBUTION T OF STUDENT; 2; DISTRIBUTION F OF FISCHER; DEGREES OF FREEDOM; INTRODUCTION TO SIMULATION TECHNIQUES OF EXPERIMENTS.

STATISTICAL INFERENCE: THEORY OF THE SAMPLES; ESTIMATION THEORY; THEORY OF DECISIONS; THE 2 TEST; ANALYSIS OF THE VARIANCE; THE FISHER TEST FOR THE VARIANCES; THE T TEST OF STUDENT; THE MC NEMAR TEST.

INTERPOLATION AND LEAST SQUARES: INTERPOLATION; EXTRAPOLATION; LEAST SQUARES; OPERATIONAL REQUIREMENTS FOR THE METHOD OF LEAST SQUARES; NUMERICAL EXAMPLES; TIME SERIES.

THEORY OF ERRORS: MEASUREMENT ERRORS; SYSTEMATIC ERRORS; ACCIDENTAL ERRORS; INDIRECT MEASUREMENTS; ERROR PROPAGATION.

APPLICATIONS: APPLICATIONS OF THE ABOVE TOPICS TO MEDICINE.

TEACHING UNIT: INFORMATICS

COMPUTER SCIENCE (BASICS AND DEFINITIONS AND): ALGORITHMS, DATA, CODING, PROGRAMMING LANGUAGES, DATABASES, DIGITAL SIGNALS AND IMAGES.

HARDWARE & SOFTWARE: COMPUTER TYPES, COMPUTER ARCHITECTURE, OPERATING SYSTEM AND BASE SOFTWARE.

APPLICATIONS AND DOCUMENTS OF COMMON USE: BASIC AND ADVANCED FUNCTIONS OF THE SPREADSHEET, USE THE SPREADSHEET FOR DESCRIPTIVE AND INFERENTIAL STATISTICS AND FOR DATA ANALYSIS.

COMPUTER NETWORKS: ARCHITECTURES AND COMMUNICATION PROTOCOLS, INTERNET AND E-MAIL, SEARCH ENGINES.

INFORMATION SYSTEMS: DATABASES AND BIBLIOGRAPHIC SEARCHES IN BIOMEDICINE.

	Teaching Methods
	LECTURES AND NUMERICAL EXERCISES.

	Verification of learning
	DURING THE COURSE SELF-ASSESSMENT TESTS WILL BE DONE. THE FINAL EXAM CONSISTS OF: A WRITTEN TEST FOR ACCESS TO ORAL INTERVIEW AIMED AT ASSESSING THE STUDENT'S ABILITY TO APPLY THE MODELS, THE THEOREMS AND THE TOOLS PRESENTED IN THE COURSE TO THE RESOLUTION OF NUMERICAL EXERCISES; AN INTERVIEW AIMED TO ASSESS THE KNOWLEDGE OF THE STUDENT OF ISSUES PRESENTED IN THE COURSE AND HIS DISCUSSION ABILITY.

Verification of learning

DURING THE COURSE SELF-ASSESSMENT TESTS WILL BE DONE.

THE FINAL EXAM CONSISTS OF:

A WRITTEN TEST FOR ACCESS TO ORAL INTERVIEW AIMED AT ASSESSING THE STUDENT'S ABILITY TO APPLY THE MODELS, THE THEOREMS AND THE TOOLS PRESENTED IN THE COURSE TO THE RESOLUTION OF NUMERICAL EXERCISES;

AN INTERVIEW AIMED TO ASSESS THE KNOWLEDGE OF THE STUDENT OF ISSUES PRESENTED IN THE COURSE AND HIS DISCUSSION ABILITY.

	Texts
	TEACHING UNIT: MEDICAL STATISTICS F. BARONE, L. MILANO, G. RUSSO, STATISTICA, ED. EDISES. JOHN R. TAYLOR, INTRODUZIONE ALL’ANALISI DEGLI ERRORI, ED. ZANICHELLI. PHILIP BEVINGTON, D. KEITH ROBINSON, DATA REDUCTION AND ERROR ANALYSIS FOR THE PHYSICAL SCIENCES, ED. MCGRAW-HILL. TEACHING UNIT: INFORMATICS INFORMATION TECHNOLOGY: THE BREAKING WAVE CURTIN, FOLEY, SEN, MORIN

	More Information
	FOR MORE DETAILED INFORMATION ON THE PROGRAM, NOTICES AND COMMUNICATIONS ABOUT THE COURSE OF MEDICAL STATISTICS AND INFORMATICS, REFER TO THE WEBSITES OF THE PROFESSORS: TEACHING UNIT: MEDICAL STATISTICS PROF. FABRIZIO BARONE HTTP://WWW.UNISA.IT/DOCENTI/FABRIZIOBARONE/INDEX TEACHING UNIT: INFORMATICS PROF. FABRIZIO ESPOSITO HTTP://WWW.UNISA.IT/DOCENTI/FABRIZIOESPOSITO/INDEX

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Fabrizio BARONE | MEDICAL STATISTICS AND INFORMATICS