Ingegneria Gestionale | STATISTICA APPLICATA E SISTEMI DI SUPPORTO ALLE DECISIONI

cod. 0622600032

STATISTICA APPLICATA E SISTEMI DI SUPPORTO ALLE DECISIONI

	0622600032
	DIPARTIMENTO DI INGEGNERIA INDUSTRIALE
	EQF7
	MANAGEMENT ENGINEERING
	2017/2018

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 APPLICATA E SISTEMI DI SUPPORTO ALLE DECISIONI
	SECS-S/02	6	60	LESSONS	SUPPLEMENTARY COMPULSORY SUBJECTS
2	STATISTICA APPLICATA E SISTEMI DI SUPPORTO ALLE DECISIONI
	MAT/09	6	60	LESSONS	SUPPLEMENTARY COMPULSORY SUBJECTS

PROFESSORS

	MAURIZIO GUIDA1 T Curriculum
	LUIGI RARITA'2 Curriculum

	Prerequisites
	FOR THE SUCCESSFUL ACHIEVEMENT OF THE OBJECTIVES, A SUITABLE KNOWLEDGE OF BASIC MATHEMATICS IS REQUIRED, AS GUARANTEED BY THE MATHEMATICS I COURSE.

	Contents
	•COMPLEMENTS OF PROBABILITY THEORY AND RANDOM VARIABLES. FUNCTIONS OF ONE RANDOM VARIABLE. COUPLES OF R.V.’S AND THEIR JOINT AND MARGINAL DISTRIBUTIONS. COVARIANCE. DISTRIBUTIONS OF DISCRETE AND CONTINUOUS R.V.’S OF COMMON USE: BERNOULLI, BINOMIAL, GEOMETRIC, NEGATIVE BINOMIAL, POISSON, UNIFORM, NORMAL, LOGNORMAL, ESPONENTIAL, GAMMA, WEIBULL. (HOURS 3/2/-) •COMPLEMENTS OF DESCRIPTIVE STATISTICS. STATISTICAL CHARACTERIZATION OF A RANDOM VARIABLE. EMPIRICAL DISTRIBUTION. PROBABILITY PLOTS: NORMAL, LOGNORMAL, ESPONENZIAL, GAMMA, WEIBULL. (HOURS 3/2/-) •BASIC ELEMENTS OF RELIABILITY THEORY. OPERATIVE DEFINITION OF RELIABILITY. RELIABILITY AND UNRELIABILITY FUNCTIONS. FAILURE PROBABILITY DENSITY. MEAN LIFE. MEAN RESIDUAL LIFE. HAZARD RATE AND CUMULATIVE HAZARD RATE FUNCTIONS. RELIABILITY MODELS FOR NON REPAIRABLE UNITS: EXPONENTIAL, WEIBULL. (HOURS 7/3/-) •RELIABILITY ANALYSIS OF MULTI COMPONENT SYSTEMS. RELIABILITY BLOCK DIAGRAMS. SERIES, PARALLEL AND SERIES-PARALLEL STRUCTURES. K-OUT-OF-N PARALLEL STRUCTURES. FAULT TREE ANALYSIS. (HOURS 7/3/-) •RELIABILITY AND AVAILABILITY ANALYSIS OF REPAIRABLE SYSTEMS. STOCHASTIC POINT PROCESSES. COUNTING PROCESSES. TIME TO FAILURE AND TIME BETWEEN FAILURES. MEAN NUMBER OF FAILURES. RATE OF OCCURRENCE OF FAILURES. FAILURE INTENSITY. HOMOGENEOUS POISSON PROCESS. RENEWAL PROCESS. NON HOMOGENEOUS POISSON PROCESS. POWER LAW PROCESS. MARKOV CHAINS AND MARKOV PROCESSES. AVAILABILITY FUNCTION. STEADY STATE AVAILABILITY AND AVERAGE AVAILABILITY. SYSTEM AVAILABILITY. (HOURS 10/5/-) •STATISTICAL METHODS FOR RELIABILITY ASSESSMENT. TYPES OF RELIABILITY DATA. NON PARAMETRIC ESTIMATION METHODS: PLOTTING POSITIONS. ANALYTICAL METHODS OF PARAMETRIC ESTIMATION: MAXIMUM LIKELIHOOD METHOD, LINEAR ESTIMATION METHODS. GRAPHICAL METHODS FOR PARAMETRIC ESTIMATION: PROBABILITY PLOTS. ESTIMATION METHODS FOR REPAIRABLE UNITS. (HOURS 10/5/-)

•COMPLEMENTS OF PROBABILITY THEORY AND RANDOM VARIABLES. FUNCTIONS OF ONE RANDOM VARIABLE. COUPLES OF R.V.’S AND THEIR JOINT AND MARGINAL DISTRIBUTIONS. COVARIANCE. DISTRIBUTIONS OF DISCRETE AND CONTINUOUS R.V.’S OF COMMON USE: BERNOULLI, BINOMIAL, GEOMETRIC, NEGATIVE BINOMIAL, POISSON, UNIFORM, NORMAL, LOGNORMAL, ESPONENTIAL, GAMMA, WEIBULL. (HOURS 3/2/-)
•COMPLEMENTS OF DESCRIPTIVE STATISTICS. STATISTICAL CHARACTERIZATION OF A RANDOM VARIABLE. EMPIRICAL DISTRIBUTION. PROBABILITY PLOTS: NORMAL, LOGNORMAL, ESPONENZIAL, GAMMA, WEIBULL. (HOURS 3/2/-)
•BASIC ELEMENTS OF RELIABILITY THEORY. OPERATIVE DEFINITION OF RELIABILITY. RELIABILITY AND UNRELIABILITY FUNCTIONS. FAILURE PROBABILITY DENSITY. MEAN LIFE. MEAN RESIDUAL LIFE. HAZARD RATE AND CUMULATIVE HAZARD RATE FUNCTIONS. RELIABILITY MODELS FOR NON REPAIRABLE UNITS: EXPONENTIAL, WEIBULL. (HOURS 7/3/-)
•RELIABILITY ANALYSIS OF MULTI COMPONENT SYSTEMS. RELIABILITY BLOCK DIAGRAMS. SERIES, PARALLEL AND SERIES-PARALLEL STRUCTURES. K-OUT-OF-N PARALLEL STRUCTURES. FAULT TREE ANALYSIS. (HOURS 7/3/-)
•RELIABILITY AND AVAILABILITY ANALYSIS OF REPAIRABLE SYSTEMS. STOCHASTIC POINT PROCESSES. COUNTING PROCESSES. TIME TO FAILURE AND TIME BETWEEN FAILURES. MEAN NUMBER OF FAILURES. RATE OF OCCURRENCE OF FAILURES. FAILURE INTENSITY. HOMOGENEOUS POISSON PROCESS. RENEWAL PROCESS. NON HOMOGENEOUS POISSON PROCESS. POWER LAW PROCESS. MARKOV CHAINS AND MARKOV PROCESSES. AVAILABILITY FUNCTION. STEADY STATE AVAILABILITY AND AVERAGE AVAILABILITY. SYSTEM AVAILABILITY. (HOURS 10/5/-)
•STATISTICAL METHODS FOR RELIABILITY ASSESSMENT. TYPES OF RELIABILITY DATA. NON PARAMETRIC ESTIMATION METHODS: PLOTTING POSITIONS. ANALYTICAL METHODS OF PARAMETRIC ESTIMATION: MAXIMUM LIKELIHOOD METHOD, LINEAR ESTIMATION METHODS. GRAPHICAL METHODS FOR PARAMETRIC ESTIMATION: PROBABILITY PLOTS. ESTIMATION METHODS FOR REPAIRABLE UNITS. (HOURS 10/5/-)

	Teaching Methods
	THE COURSE INCLUDES THEORETICAL LESSONS AND CLASSROOM EXERCISES. SOME CLASSROOM EXERCISES INVOLVING SIMPLE STATISTICAL ANALYSES ARE SOLVED BY USING STATISTICAL SOFTWARE.

	Verification of learning
	THE GOAL OF THE FINAL EXAM IS THE EVALUATION OF THE KNOWLEDGE AND UNDERSTANDING OF THE CONCEPTS PRESENTED DURING THE COURSE, THE ABILITY TO APPLY THAT KNOWLEDGE TO SOLVE PROBLEMS ON PROBABILITY, TO ESTIMATE UNKNOWN MODEL PARAMETERS, TO MAKE DECISION ON THE BASIS OF HYPOTHESES TESTING, TO STUDY THE EFFECTS OF PRIMARY FACTORS ON PHYSICAL AND/OR TECHNOLOGICAL PHENOMENA AND TO ASSESS SIMPLE EMPIRICAL MODELS FOR THEM. FURTHERMORE, THE PERSONAL JUDGEMENT, THE COMMUNICATION SKILLS AND THE LEARNING ABILITIES ARE ALSO EVALUATED. THE FINAL EXAM CONSISTS OF A WRITTEN TEST WHICH AIMS TO ASSESS THE ABILITY TO SOLVE PROBLEMS ABOUT THE TOPICS PRESENTED DURING THE COURSE, SUCH AS: 1) BASIC PROBABILITY EVALUATIONS; 2) BASIC STATISTICAL INFERENCE AND DECISION MAKING; 3) BASIC ANOVA AND LINEAR REGRESSION ANALYSES. THE WRITTEN TEST IS EVALUATED ON THE BASIS OF THE CORRECTNESS OF THE APPROACH AND THE RESULTS ACCORDING TO A SCORE, EXPRESSED OUT OF THIRTY. THE “INSUFFICIENT” SCORE IMPLIES THE WRITTEN TEST REPETITION. AFTER THE WRITTEN TEST, STUDENTS MAY ASK TO DO AN ORAL INTERVIEW, TOO. THIS INTERVIEW WILL BE ADDRESSED TO VERIFY THE ACQUIRED KNOWLEDGE ALSO ON THE TOPICS NOT COVERED BY THE WRITTEN TEST. IN SUCH CASE, THE WRITTEN TEST WILL CONTRIBUTE FOR 60% TO THE FINAL SCORE, WHILE THE ORAL INTERVIEW FOR 40%. AN ORAL INTERVIEW THAT IS NOT CONSIDERED SUFFICIENT IMPLIES THE REPETITION OF THE WRITTEN TEST, TOO. FULL MARKS WITH DISTINCTION MAY BE GIVEN TO STUDENTS WHO DEMONSTRATE THAT THEY CAN APPLY THE ACQUIRED KNOWLEDGE WITH CONSIDERABLE AUTONOMY TO EXERCISES AND THEORETICAL ISSUES.

Verification of learning

THE GOAL OF THE FINAL EXAM IS THE EVALUATION OF THE KNOWLEDGE AND UNDERSTANDING OF THE CONCEPTS PRESENTED DURING THE COURSE, THE ABILITY TO APPLY THAT KNOWLEDGE TO SOLVE PROBLEMS ON PROBABILITY, TO ESTIMATE UNKNOWN MODEL PARAMETERS, TO MAKE DECISION ON THE BASIS OF HYPOTHESES TESTING, TO STUDY THE EFFECTS OF PRIMARY FACTORS ON PHYSICAL AND/OR TECHNOLOGICAL PHENOMENA AND TO ASSESS SIMPLE EMPIRICAL MODELS FOR THEM. FURTHERMORE, THE PERSONAL JUDGEMENT, THE COMMUNICATION SKILLS AND THE LEARNING ABILITIES ARE ALSO EVALUATED.

THE FINAL EXAM CONSISTS OF A WRITTEN TEST WHICH AIMS TO ASSESS THE ABILITY TO SOLVE PROBLEMS ABOUT THE TOPICS PRESENTED DURING THE COURSE, SUCH AS: 1) BASIC PROBABILITY EVALUATIONS; 2) BASIC STATISTICAL INFERENCE AND DECISION MAKING; 3) BASIC ANOVA AND LINEAR REGRESSION ANALYSES. THE WRITTEN TEST IS EVALUATED ON THE BASIS OF THE CORRECTNESS OF THE APPROACH AND THE RESULTS ACCORDING TO A SCORE, EXPRESSED OUT OF THIRTY. THE “INSUFFICIENT” SCORE IMPLIES THE WRITTEN TEST REPETITION.

AFTER THE WRITTEN TEST, STUDENTS MAY ASK TO DO AN ORAL INTERVIEW, TOO. THIS INTERVIEW WILL BE ADDRESSED TO VERIFY THE ACQUIRED KNOWLEDGE ALSO ON THE TOPICS NOT COVERED BY THE WRITTEN TEST. IN SUCH CASE, THE WRITTEN TEST WILL CONTRIBUTE FOR 60% TO THE FINAL SCORE, WHILE THE ORAL INTERVIEW FOR 40%. AN ORAL INTERVIEW THAT IS NOT CONSIDERED SUFFICIENT IMPLIES THE REPETITION OF THE WRITTEN TEST, TOO.

FULL MARKS WITH DISTINCTION MAY BE GIVEN TO STUDENTS WHO DEMONSTRATE THAT THEY CAN APPLY THE ACQUIRED KNOWLEDGE WITH CONSIDERABLE AUTONOMY TO EXERCISES AND THEORETICAL ISSUES.