Degree Course in Statistics for Business and Insurance Table of Contents Degree Course in Statistics for Business and Insurance Courses, Lecturers, Semesters Courses Content 2 4 6 Bachelor Degree Course in Statistics for Business and Insurance Admission requirements To be admitted to the degree course in Statistics for Business and Insurance, it is necessary to have a high school diploma or other academic qualification obtained abroad and recognized as valid. To access the Degree Course in Statistics for Business and Insurance it is necessary to have a good knowledge of the Italian language, both written and oral, basic level of English and solid knowledge of logics, mathematics and informatics. Course Profile The Degree Course offers: a thorough understanding of methods and procedures in statistics, the skills of methodological instruments for projecting and carrying out statistical investigations, competence in measurement and processing of quantitative and qualitative data; a solid knowledge in basic subjects; a good knowledge regarding firms, financial markets and insurance companies; adequate backgrounds of methodologies, techniques, instruments of informatics applied in public and private companies and financial and insurance markets. The degree course offers basic courses in statistics, mathematics and informatics that provide deep knowledge of statistic and actuarial techniques to analyse insurance and financial markets and also the knowledge of statistical methodologies and informatics tools for business management and market analysis. The deep study of actuarial and financial disciplines offers students necessary tools for creation and administration of insurance systems, of social and private pensions, for analysis of financial markets and for accessing Junior Actuary profession. The deep study of statistical disciplines and of methodologies of informatics gives necessary tools for efficient and effective use of information systems of private and public firms that permit to create, update and administrate databases, to analyse markets data, to evaluate potentialities and expansion of new markets and to forecast goods consumption and investments. The use of the laboratory is aimed to developing, studying and analysing real or simulated cases. Expected achievements Knowledge and understanding The student acquires solid practical and theoretical knowledge in mathematics, statistics, informatics and business as well as the knowledge related to: Statistical and actuarial techniques for insurance and financial markets; Statistical methodologies and informatics tools for firm management and market analysis. The capacity to apply the knowledge and the understanding will contribute to develop the ability in elaborating information, managing and interpreting economic and financial data of the firm and the markets where the firm operates. Moreover, it will contribute to develop capabilities of construction and administration of statistical systems of data. Formulation of personal opinion The student develops ability to formulate personal opinion, to approach critically, and obtains skills to work in groups. This improves capability to evaluate and to manage uncertainty, to conduct surveys, to process and to interpret data related to firm and to market analysis. Communication skills The student develops adequate competences and necessary tools for correct transmission of information and for the transmission of statistical, financial and actuarial data both in written and oral form. Learning skills The student develops necessary learning skills to continue studies of master degree and to be involved into labour market with high degree of autonomy and solid cultural backgrounds, which permit to the student to adapt and update continually. 2 Employment opportunities The graduate can be placed at the labour market as a self-employed as well as employed professional. For graduates in Statistics for Business and Insurance the principal employers are the insurance companies that operate in insurance and pension fields, as well as banks and other institutions operating in the area of finance. The degree in Statistics for Business and Insurance gives the access to the state examination to obtain the profession of Junior Actuary. Moreover, the graduates may work in companies operating different fields: production, marketing, management control, data elaboration and information systems. Particularly, the graduates are capable to utilise the necessary statistical tools, for example, to analyse possibility of company penetration in markets, evaluate effects of promotion and marketing policies, analyse the division of markets shares between the competitors. Access to successive studies The degree allows to access second-cycle studies (Master), particular in the field of statistics. Requisites to obtain final degree To obtain the Bachelor Degree in Statistics for Business and Insurance, the student must acquire 180 credits, including acquiring the knowledge of one of the European Union languages, as well as the Italian language. 3 DIDACTIC OFFER LIST OF COURSES ACTIVATED IN 2014/2015 I year (enrolled in 2014/2015) Course Type of courses Field of courses Sector Code ECTS Lecturer Cycle Code MATHEMATICAL ANALYSIS Basic Mathematics MAT/05 10 PIETRAMALA Paolamaria 1° - 2° 5 Borrowed from Demography (0746) 4° 10 FABBRINI Giuseppe 1°-2° 10 RICOTTA Fernanda 3° - 4° Statistics, Applied Statistics, SECS-S/04 Demographic Economics and BUSINESS ECONOMICS Characterising SECS-P/07 Business PRINCIPLES OF Economics and Characterising SECS-P/01 ECONOMICS Business INTRODUCTION TO Informatics and STATISTICAL Other activities SECS-S/01 telematics skills COMPUTING 1 DEMOGRAPHY Characterising 2 TARSITANO Agostino 4° L-LIN/12 5 Borrowed from English Language, Economics Degree Course (0744) 1° - 2° Statistics and Probabilistic SECS-S/01 10 LATORRE Giovanni 1° - 2° Field of courses Sector Code ECTS Lecturer Cycle Code 9 PIETRAMALA Paolamaria 1° - 2° 10 RUSSO Wilma 3° - 4° 10 COSSARI Antony 3° - 4° 3 TARSITANO Agostino 2° 10 COSTABILE Massimo 1° -2° 10 TARSITANO Agostino 3° - 4° ECONOMIC STATISTICS Statistics, Applied (curriculum Statistics, Characterising Statistics, SECS-S/01 Finance and Insurance) Demographic 10 Borrowed from Statistics for Firms and Insurance Degree (0746) 3° - 4° STATISTICS AND PROBABILITY Composed in coordinated Statistics, Applied modules: Statistics, SECS-S/01 Characterising a) STATISTICS AND Demographic PROBABILITY (5 ECTS) SECS-S/06 Basic b) PROBABILISTIC Mathematics METHODS FOR ECONOMICS (5 ECTS) 10 LECCADITO Arturo 1° - 2° COSSARI Antony ENGLISH LANGUAGE LABORATORY STATISTICS Other activities Foreign language Basic II year (enrolled in 2013/2014) Course Type of courses MATHEMATICAL ANALYSIS AND LINEAR Basic Mathematics MAT/05 ALGEBRA FUNDAMENTALS OF Basic Informatics ING-INF/05 COMPUTER SCIENCE STATISTICAL Statistics and Basic SECS-S/01 INFERENCE Probabilistic INTRODUCTION TO Informatics and STATISTICAL Other activities SECS-S/01 telematics skills COMPUTING 2 FINANCIAL Basic Mathematics SECS-S/06 MATHEMATICS STATISTICS FOR Statistics, Applied BUSINESSES Characterising Statistics, SECS-S/01 (curriculum Administration Demographic and Analysis of Data) III year (enrolled in 2012/2013) Course Type of courses MULTIVARIATE DATA ANALYSIS Characterising Field of courses Sector Code Statistics, Applied SECS-S/01 Statistics, ECTS Lecturer Cycle Code 10 TARSITANO Agostino 1° - 2° 4 INTRODUCTION TO DATABASE SYSTEMS DEMOGRAPHY ACTUARIAL MATHEMATICS Demographic Informatics and Characterising Applied ING-INF/05 Mathematics Statistics, Applied Characterising Statistics, SECS-S/04 Demographic Refining and Refining integrating SECS-S/06 activities Refining and Refining integrating IUS/01 activities PRIVATE AND INSURANCE LAW (group A) ACTUARIAL TECHNIQUES OF NONCharacterising LIFE INSURANCE (group A) Informatics and Applied SECS-P/06 Mathematics CORPORATE FINANCE (group B) Refining Refining and integrating activities OPERATIONS RESEARCH (group B) Basic Informatics and Applied Mathematics 10 GRECO Sergio MOLINARO Cristian 3° - 4° 5 STRANGES Manuela 4° 10 PIRRA Marco 1°- 2° 10 MAISTO Filippo 3° - 4° 10 CERCHIARA Rocco 1° - 2° 1°- 2° 1° -2° SECS-P/09 10 Borrowed from Business Finance, Business Economics Degree Course (0749) MAT/09 10 PALETTA Giuseppe 5 Bachelor Degree content course in Statistics for Business and Insurance 1st year Course Code 27002208 Course Name Mathematical Analysis ISCED Code CFU (ECTS) 10 Course Year 1st Year Degree in Statistics for Business and Insurance Semester Winter Lecturer Prof. PIETRAMALA Paolamaria Activity Type Teaching Total Hours / 60 / 6 Hours per Week Apprenticeship NO Language of Italian Instruction Course Contents: Powers and Polynomials, Exponentials and Logarithms, Hyperbolic Functions, Trigonometric Functions and inverses. Limits, Continuous Functions. The Derivative of a Function, The Slope and the Tangent Line, The Product and Quotient and Power Rules, Derivatives by the Charin Rule, Inverse Functions and Their Derivatives. Applications of the Derivative: Linear Approximation, Maximum and Minimum Problems, Second Derivatives, Graphs, The Mean Value Theorem and l'Hôpital's Rule. Integrals: The Idea of an Integral, Antiderivatives, Indefinite Integrals and Substitutions, Techniques of Integration, Integration by Parts, Partial Fractions. The Definite Integral, Properties of the Integral and the Average Value, The Fundamental Theorem and Its Consequences, Improper Integrals. Applications of the Integral:Areas. Sequences and Infinite Series, The Geometric Series, Convergence Tests: Positive Series, Convergence Tests: All Series, Recommended or Bertsch-Dal Passo: Elementi di Analisi Matematica, Aracne Editrice. MarcelliniRequired Reading Sbordone: Calcolo, Liguori Editore. Cecconi-Stampacchia: Analisi Matematica, Liguori Editore. Marcellini-Sbordone: Esercitazioni di Matematica, vol. primo (parte prima e seconda), Liguori Editore. Cecconi-Piccinini- Stampacchia: Esercizi e problemi di Analisi Matematica,vol. primo, Liguori Editore. Prerequisites Exam of Mathematical Analysis Teaching Lectures, tutorials Methods Assessment Written and oral Methods More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/pietramala/ 6 Course Code 27003078 Course Name Demography ISCED Code CFU (ECTS) 5 Course Year 1st Year Degree in Statistics for Business and Insurance Semester Spring Lecturer Prof. STRANGES Manuela Activity Type Teaching Total Hours / Hours 30 / 6 per Week Apprenticeship NO Language of Italian Instruction Course Contents: Aims and goals of demography. The statistical sources for the demographic analysis: ancient and modern sources, ecclesiastical sources, statistical and administrative sources. Notions and basic tools for analysis: the concepts of time, duration and age, intensity and timing of demographic phenomena; pure measures and measurements in the presence of interference, independence or continuity hypothesis. Analysis of the population structure: age distribution, structure indices, age ratios, sex distribution, sex ratios, the population pyramid. Basic analysis of demographic phenomena: crude rates, specific rates, total rates; relationship between generic and specific rates; Direct and indirect standardization. Elements of longitudinal and transversal analysis: measures for period analysis and cohort analysis; the Lexis diagram and its extensions. Measures of demographic growth: equation of population; arithmetic, geometric and continuous growth measures; natural and migration components of population growth; the logistic model. Mortality: notes on the historical origins and uses of life tables, the life table and its biometric functions; measurements in the presence of interference; functions in the discrete and continuous time; relationship between mortality rates and the probability of death; abbreviated mortality tables; the stationary population; the point of Lexis. Infant mortality: measures (infant mortality rate, perinatal, neonatal, early neonatal, late neonatal rates, etc..); infant mortality by cause; the biometric pattern of Bourgeois-Pichat. Marriage: marriage rates; flow statistics and status, intensity and frequency of marriage; analysis of contemporary marriage, the marriage table, special measures of marriage, dissolution of marriage; basic measurements of the divorce. Fertility: analysis of fertility by generation, period analysis of fertility, intensity and frequency of fertility, general and specific rates, special measures of fertility, legitimate and illegitimate fertility, fertility by birth order, probability to increase fertility. Migration: mobility and migration; intensity and frequency of migration; longitudinal and transversal analysis of migration; special measures (efficiency index, index of differential migration, redistribution). Forecasts and demographic projections: the synthetic method and the analytical or cohort-components method; estimates of births; forecasts with the migratory movement. Models of population: stable population, stationary population. Further topics related to the development of contemporary demography and interrelationships between population, economy and society. Recommended or De Santis G., “Demografia”, Serie Manuali, Il Mulino, Bologna, 2010. Stranges M., Required Reading “Elementi di Demografia e Statistica per il Territorio”, CELUC – Centro Editoriale e Librario, Università della Calabria, Arcavacata di Rende (Cosenza), 2005. De Bartolo G., “Elementi di analisi demografica e demografia applicata”, CELUC – Centro Editoriale e Librario, Università della Calabria, Arcavacata di Rende (Cosenza), 1997. Additional material will be suggested by the teacher during the Prerequisites Teaching Methods Assessment Methods More Information lessons none lectures + exercises written examination Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/stranges/ 7 Course Code 27003003 Course Name Business Economics ISCED Code CFU (ECTS) 10 Course Year 1st Year Degree in Statistics for Business and Insurance Semester Winter Lecturer Prof. FABBRINI Giuseppe Activity Type Teaching Total Hours / Hours 60 / 6 per Week Apprenticeship NO Language of Italian Instruction Course Contents: Human needs and the company. Legal entity and economic entity. The legal forms: individual and collective company, partnerships and corporations. The classification of companies: companies manufacturing and delivery, public and private companies. Business groups. The configuration of the groups and their classification. Notes on the theory of systems. The business system and its features. The decomposition of the business system into sub-systems. The interactions between business and the environment. The environment of the company. The sub-areas of the general environment. The specific environment of the company. The basic concepts of business organization, the organizational variables. The main models of organizational structure: multi-purpose, multi-divisional and matrix. Operating systems: information system, communication system, system planning, scheduling and control system of personnel management. Leadership styles: authoritarian, democratic and permissive. The categories of transactions in business management: provision, financing, processing and trade. The financial and economic aspects of management: cash on hand, the economic values of income and capital, the financial values. The share in terms of quantity and quality. Investments and funding. Classifications of investment and financing, assets, liabilities and fund equity values. The total income and income statements. The relationship between capital and income. The economy and the conditions of economic equilibrium. The financial requirements, its coverage and conditions of financial equilibrium. The objects and purposes of the survey. Systems and the method of detection, revenue accounting system, system of capital and earnings, double entry method. Examples of operating records and writings of adjustment. The formation of the financial statements (notes). Recommended or G. Fabbrini – A. Montrone (a cura di), ECONOMIA AZIENDALE – I FONDAMENTI Required Reading DELLA DISCIPLINA, Volume I, Franco Angeli, 2006 Prerequisites None Teaching Methods Lectures by the professor responsible for the course. Theory lessons will always be accompanied by resolutions of case studies and exercises of accounting. Assessment Methods Written test and oral More Information Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/fabbrini/ 8 Course Code Course Name ISCED Code CFU (ECTS) Course Year Semester Lecturer Activity Type Total Hours / Hours per Week Apprenticeship Language of Instruction 27004003 Principles of Economics 10 1st Year Degree in Statistics for Business and Insurance Spring Prof. RICOTTA Fernanda Teaching 60 / 6 NO Italian Course Contents: Microeconomics part: the Basics of Supply and Demand; Consumer Behavior Individual and Market Demand; Production; The Cost of Production; Profit Maximization and Competitive Supply; The Analysis of Competitive Markets; Market Power: Monopoly; Externalities. Macroeconomics part: The Goods Market; Financial Markets; Goods and Financial Markets (IS-LM Model); Goods and Financial Markets in an Open Economy; The Labor Market. Recommended or Microeconomics part: Robert S. Pindyck, Daniel L. Rubinfeld, Microeconomia Required Reading 8/Ed., Pearson Education Italia, 2013. Macroeconomics part: O. Blanchard, Scoprire la macroeconomia, il Mulino, 2009, vol. I. Prerequisites None Teaching Methods The course consists of formal lectures and tutorials. Active participation in discussion and classwork is required. Slides and other information on the course available at http://www.ecostat.unical.it/ricotta/ Assessment Methods Final written exam of two hours. Exams will be made of theoretical questions More Information and exercises. Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/ricotta/ 9 Course Code 27003106 Course Name Introduction to Statistical Computing ISCED Code CFU (ECTS) 2 Course Year 1st Year Degree in Statistics for Business and Insurance Semester Spring Lecturer Prof. TARSITANO Agostino Activity Type Teaching Total Hours / Hours 12 / 2 per Week Apprenticeship NO Language of Italian Instruction Course Contents: Applications of explorative statistics statistical, graphical methods, simple simulations, models of random variables Recommended or Iacus S. M., Masarotto G. (2008) "Laboratorio di Statistica con R". McGraw-Hill , Required Reading Milano. Everit B. S., Hothorn T. (2006) "A Handbook of Statistical Analyses Using R". Chapman & Hall/Crc, Boca Raton (FL) Prerequisites Basic Statistics Teaching Methods Laboratory: Familiarity with the statistical calculation through intensive practical experiences Assessment Intermediate and final computer test of the type pass/fail Methods More Information Other optional Teaching Units: Introductory probability Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/tarsitano/ 10 Course Code 27003006 Course Name English ISCED Code CFU (ECTS) 5 Course Year 1st Year Degree in Statistics for Business and Insurance Semester Winter Lecturer Prof. Activity Type Teaching Total Hours / Hours per Week 30 / 6 Apprenticeship NO Language of Instruction Italian Course Contents: The teaching approach is communicative and learner-centered. The lessons are aimed at developing writing and speaking skills. Specifically: Speaking: • Introducing yourself • Giving and asking for personal information • Describing and asking about jobs and responsibilities • Expressing opinions • Taking turns in a discussion Listening: • Understanding brief messages • Taking notes • Understanding the main idea Reading: • Understanding short notices, messages, etc. • Finding and understanding the main idea of a text • Finding specific information • Identifying key words • Recognizing synonyms • Analyzing graphs • Taking notes of important points Writing • Writing e-mails The course content focuses on academic topics in order to introduce study skills which facilitate the acquisition of a foreign language. Recommended or Required Language Leader (Pre-intermediate) Pearson/Longman Reading Prerequisites None Teaching Methods Tutorials and self-study. Assessment Methods The written exam assesses the knowledge of the following linguistic aspects: text cohesion, general and academic lexis, analysis of a graph, understanding and analysis of a text. More Information Attendance: compulsory Lecturer webpage: 11 Course Code 27003002 Course Name Statistics ISCED Code CFU (ECTS) 10 Course Year 1st Year Degree in Statistics for Business and Insurance Semester Spring Lecturer Prof. LATORRE Giovanni Activity Type Teaching Total Hours / Hours 60 / 6 per Week Apprenticeship NO Language of Italian Instruction Course Contents: Descriptive Statistics. The role of Statistics and data analysis process. Types of data. Frequency distributions: absolute, relative, cumulative, density. Graphical method for visualizing data: bar and pie charts, cumulative frequency plot, histograms. Describing the center of a data set Mode, median, percentiles, Chisini means, means of order s. The arithmetic mean and its properties: internality, minimum, associative, linearity. The geometric mean. Describing the variability in a data set range, interquartile range, absolute deviations of order s, mean differences, the variance and the standard deviation, the coefficient of variation. The Gini homogeneity index Bivariate data Contingency tables, marginal and conditioned distributions. The concept of statistical dependence and its assessment. The maximum statistical dependence. Different formulations of the Chi-square index. The Cramer index. The concept of mean dependence and the its measure. The study of the correlation: the covariance and its sign, the Cauchy-Schwartz inequality, the Pearson correlation coefficient. The linear regression: fitting a line to bivariata data, the principle of least squares and the determination of the parameters, assessing the fit of a line, the residual plot Recommended or Agresti A., Franklin C. (2009) “Statistics. The Art and Science of Learning from Required Reading Data”, Pearson Education Bennet J.O., Briggs W.L., Triola M.F. (2009) “Statistical Reasoning for Everyday Life”, Pearson Education Cicchitelli G. (2008) “Statistica. Principi e Metodi”. Pearson Education Latorre G. “Probabilità e Statistica. Vol. 3. 1”. Disponibile in copisteria Leti G., Cerbara L. (2009). Elementi di Statistica Descrittiva”, Il Mulino Peck R., Devore J. (2008) “Statistics. The Exploration and Analysis of Data”, Thomson Zenga M. (2007). “Lezioni di Statistica descrittiva”. G. Giappichelli Editore, Torino. Prerequisites None Teaching Methods Theoretical lectures and solution of exercises Assessment Written and oral Methods More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/latorre/ 12 2nd year Course Code 27003110 Course Name Mathematical Analysis and Linear Algebra ISCED Code CFU (ECTS) 10 Course Year 2nd Year Degree in Statistics for Business and Insurance Semester Winter Lecturer Prof. PIETRAMALA Paolamaria Activity Type Teaching Total Hours / 54 + 6 / 6 Hours per Week Apprenticeship NO Language of Italian Instruction Course Contents: Ellipses, Parabolas, and Hyperbolas. Vectors and Matrices, Determinants, Matrices and Linear Equations. Eigenvalues and Eigenvectors Multi-variable functions: Partial Derivatives, Tangent Planes and Linear Approximations, Directional Derivatives and Gradients, The Chain Rule, Maximum and Minimum Problems, Maxima, Minima, and Saddle Points, Constraints and Lagrange Multipliers. Double Integrals, Changing to Better Coordinates, Polar Coordinates, Improper double integrals. Recommended or Bertsch-Dal Passo: Elementi di Analisi Matematica, Aracne Editrice. ChiritaRequired Ciarletta: Calcolo, Zanichelli Editore. Bramanti-Pagani-Salsa: Matematica, Calcolo Reading infinitesimale e Algebra Lineare, Zanichelli Editore. Marcellini-Sbordone: Esercitazioni di Matematica, vol. secondo (parte prima e seconda), Liguori Editore. Prerequisites Exam of Mathematical Analysis Teaching Lectures and tutorials Methods Assessment Written and oral Methods More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/pietramala/ 13 Course Code Course Name ISCED Code CFU (ECTS) Course Year Semester Lecturer Activity Type Total Hours / Hours per Week Apprenticeship Language of Instruction 27000002 FUNDAMENTALS OF COMPUTER SCIENCE ING-INF/05 10 2nd Year Degree in Statistics for Business and Insurance Spring Prof. RUSSO Wilma Teaching 60 / 6 NO Italian Course Contents: Overview of computers and programming: information coding, algorithms, programming languages, operating systems and networks. Elements of programming in Java: variables; assignment statements; primitive data types; conditionals and loops instructions; methods; singledimensional and multi-dimensional arrays; input/output operations. Object-oriented programming in Java: classes, objects, encapsulation, inheritance and polymorphism. Recommended or Lecture notes of the teacher; Bertacca, Guidi, Introduzione a Java, McGraw-Hill, Required Reading Horstmann, Cornell Java 2 i fondamenti McGraw-Hill, Cabibbo: “Fondamenti di informatica Oggetti e Java”, McGraw-Hill Prerequisites none Teaching Methods Front lectures and exercises, self study, homework and practical activities at the Laboratory of Computer Science (LDI) Assessment The examination consists of a practical test (to be held at the Laboratory of Methods Computer Science) and an oral test. More Information Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/russo/ 14 Course Code Course Name ISCED Code CFU (ECTS) Course Year Semester Lecturer Activity Type Total Hours / Hours per Week Apprenticeship Language of Instruction 27003111 Statistical Inference 10 2nd Year Degree in Statistics for Business and Insurance Spring Prof. COSSARI Anthony Teaching 60 / 6 NO Italian Course Contents: Probability. Univariate and multivariate random variables; Student t, Fisher F. Point estimation. Random sample, sample statistics and sample moments, especially sample average and sample variance. Parametric estimation. Sample space and parametric space. Estimators and their properties: mean squared error, unbiasedness, efficiency, consistency. Cramer-Rao inequality. Sufficiency and completeness, UMVUE estimator. Estimation methods: moments method and maximum likelihood method. Interval estimation. Confidence level, confidence interval, pivotal quantity, applications from normal distribution. Hypothesis testing. Parametric hypotheses. Test of significance: test statistics, significance level and p-value, rejection region. Applications from Normal distribution. Fundamentals of theory of hypothesis testing: first and second type error, test power, optimal critical region, uniformily more powerful test. test. Analysis of variance. One factor ANOVA model, Hypotheses on the model. ANOVA test, randomization. Two-factor extension, blocking. Regression model. Model specification. Basic hypotheses. Least squares estimation method. Properties of least squares estimator. Variance decomposition. R^2 index. Hypothesis of normal errors. Significance testing on model parameters. ANOVA test. Analysis of residuals. Applications to real problems Recommended or - Cicchitelli G., Probabilità e statistica, II edizione, Maggioli Editore (2001) Required Reading Mood A.M., Graybill F.A., Boes D.C., Introduzione alla statistica, McGraw-Hill Italia (1988) - Slides of the talks Prerequisites Exam of Statistics Teaching Methods Lectures Assessment Methods More Information Written and oral exam Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/cossari/ 15 Course Code 27003107 Course Name Introduction to Statistical Computing 2 ISCED Code CFU (ECTS) 2 Course Year 2nd Year Degree in Statistics for Business and Insurance Semester Winter Lecturer Prof. TARSITANO Agostino Activity Type Teaching Total Hours / 18 / 2 Hours per Week Apprenticeship NO Language of Italian Instruction Course Contents: practical applications of some of the most recurrent packages; elements of programming in the R environment. Recommended or Iacus S. M., Masarotto G. (2008) "Laboratorio di Statistica con R". McGraw-Hill , Required Reading Milano. Everit B. S., Hothorn T. (2006) "A Handbook of Statistical Analyses Using R". Chapman & Hall/Crc, Boca Raton (FL) Prerequisites Inferential statistics, multivariate analysis, Business and economic statistics Teaching Methods Laboratory: Advances with the statistical calculation through intensive practical experiences Assessment intermediate and final computer test of the type pass/fail Methods More Information Other optional Teaching Units: Statistical Inference, Multivariate Data Analysis, linear algebra Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/tarsitano/ 16 Course Code 27003011 Course Name Financial Mathematics ISCED Code CFU (ECTS) 10 Course Year 2nd Year Degree in Statistics for Business and Insurance Semester Winter Lecturer Prof. MENZIETTI Massimiliano Activity Type Teaching Total Hours / 60 / 6 Hours per Week Apprenticeship NO Language of Italian Instruction Course Contents: 1. Basic concepts of financial mathematics. Interest, interest rate, discount rate, instantaneous interest rate, in spot and future basic financial operation. The simple interest function and the compound interest function. The exponential interest function. Equivalent rates in simple and compound interest functions. Nominal rates. Zero coupon bond and coupon bond. 2. The value of a financial operation. Present value and future value. Fair financial operation respect to a financial function. Properties of the exponential interest function. Net present value as choice criterion between financial operations. 3. Annuity and mortgage loan. Annuity definitions. Present value and future value of temporary annuity (anticipated, posticipated, immediate and deferred, temporary and perpetual). Mortgage loan definitions. Amortization schedule. Mortgage loan with constant payment, Mortgage loan with constant principal, Mortgage loan with final payment. 4. Internal Rate of Return. Definition of Internal Rate of Return (IRR) in a financial operation. condition of existence and uniqueness of the IRR. Cartesium theorem. Cases with analytical solution for the IRR. Numerical methods for the determination of the IRR: the secant method. The IRR as choice criterion between financial operations. 5. Time and volatility index. Maturity, time to maturity, average maturity and Macaulay duration. Portfolio Duration, Fixed bond duration. The Macaulay duration as volatility index. Percentage variation of the cash flow value. 6. Value function and market prices. Market assumption: frictionless, competitiveness and arbitrage free. Zero coupon bond. The linearity of the present value. Value function in spot and forward contract. The term structure of interest rate. 7. Introduction to the immunization theory. Interest rate risk. Classic immunization theory. The theorem of Fisher and Weil and Redington’s theorem. 8. Elements of utility theory. The problems of the choice between stochastic financial operation. Remarks on the axiomatic approach. Preference ordering on the opportunity set. First order stochastic dominance. Theorem of von Neumann and Morgenstern. The expectation criterion. The Saint Petersburg paradox. The expected utility criterion (certainty equivalent). Risk aversion, and risk propensity. Utility function differential properties. Absolute measure of risk aversion. Some kinds of utility functions: (logarithmic, exponential and quadratic). Quadratic approximation of the utility function. Mean-variance criterion. Minimum variance portfolio (the two assets case). Insurance policies and utility theory: elements. Recommended or Moriconi F., De Felice M., La teoria dell’immunizzazione finanziaria, Il Mulino, 1991 Required Reading Moriconi F., Matematica finanziaria, Il Mulino, 1995. Cacciafesta F., Matematica Finanziaria (classica e moderna) per i corsi triennali, Giappichelli, 2006 Massabò I., Costabile M., Esercizi di Matematica Finanziaria Prerequisites None Teaching Self-study, lectures and exercises Methods Assessment Written and oral examination Methods More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/menzietti/ 17 Course Code 27003114 Course Name Statistics for Businesses ISCED Code CFU (ECTS) 10 Course Year 2nd Year Degree in Statistics for Business and Insurance Semester Spring Lecturer Prof. TARSITANO Agostino Activity Type Teaching Total Hours / 60 / 6 Hours per Week Apprenticeship NO Language of Italian Instruction Course Contents: 1) Business intelligence and statistical applications in quality management. 2) Ration analysis. 3) Shift-share analysis and related topics 4) Spatial correlation 5) Index numbers and their applications 6) Measurement of industrial concentration 7) Sampling techniques 8) Rank related statistics. 9) Hierarchic cluster analysis and CART techniques 10) Time series and forecasting Recommended or Required Reading Prerequisites An introductory course of Statistics Teaching Methods The lectures, mostly PPT based, focus on elaboration of key concepts and principles, and extensive illustration of their applications by way of topical examples. The lectures will be supplemented with a few case studies to apply the theoretical concepts for understanding practical situations and practical applications in the R evironment. Assessment Written and oral Methods More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/tarsitano/ 18 Course Code Course Name ISCED Code CFU (ECTS) Course Year Semester Lecturer Activity Type Total Hours / Hours per Week Apprenticeship Language of Instruction Course Contents: Recommended or Required Reading Prerequisites Teaching Methods Assessment Methods More Information 27003112 Economic Statistics 10 2nd Year Degree in Statistics for Business and Insurance Spring Prof. TARSITANO Agostino Teaching 60 / 6 NO Italian Exam of Statistics Lectures and laboratory Written and oral Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/tarsitano/ 19 INTEGRATED SUBJECT Course Code Course Name ISCED Code CFU (ECTS) Course Year Semester Prerequisites Assessment Methods 27003109 Statistics and Probability 10 2nd Year Degree in Statistics for Business and Insurance Spring none written and oral exam MODULE Course Code 27000006 Course Name Statistics and Probability ISCED Code CFU (ECTS) 5 Course Year 2nd Year Degree in Statistics for Business and Insurance Semester Spring Lecturer Prof. COSSARI Anthony Activity Type Teaching Total Hours / 30 / 6 Hours per Week Apprenticeship NO Language of Italian Instruction Course Contents: Uncertainty and casuality, set theory, space of events, events and their properties; Probability: definitions and basic properties, combinatorics; Conditional probability: definitions and properties; Independence: definitions and properties, Bayes theorem; Discrete random variables: random variables, probability function, cumulative distribution function, expected value and variance; Discrete models: uniform, Bernoulli, Binomial, Poisson, geometric; Continuos random variables: Probability density function, cumulative distribution function, expected value and variance; Continuos models: uniform, exponential, normal, gamma, approximations, Chebyshev inequality. Recommended - Cicchitelli G., Probabilità e statistica, II edizione, Maggioli Editore (2001) or Required - Mood A.M., Graybill F.A., Boes D.C., Introduzione alla statistica, McGraw-Hill Reading Italia (1988) - Slides of the talks. Prerequisites None Teaching 30 hours of front lectures Methods Assessment Methods More Information Written and oral exam Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/cossari/ 20 MODULE Course Code 27003108 Course Name Probabilistic Methods for Economics ISCED Code CFU (ECTS) 5 Course Year 2nd Year Degree in Statistics for Business and Insurance Semester Spring Lecturer Prof. LECCADITO Arturo Activity Type Teaching Total Hours / 30 / 6 Hours per Week Apprenticeship NO Language of Italian Instruction Course Contents: -The moment generating function (mgf). The mgf of some important probability distributions (binomial; Poisson; geometric and negative binomial; uniform; normal; gamma and exponential; beta; and Cauchy distributions) -Functions of random variables, sum of random variables -Multiple random variables -Chebyshev Inequality -Limit Theorems Recommended -Weiss Neil A., Calcolo delle probabilità – Published by Pearson Education, 2008 or Required (English Version: Reading Weiss Neil A., A Course in Probability – Published by Addison-Wesley, 2006 -Lecture Notes Prerequisites None Teaching Frontal lecture Methods Assessment Written and oral exam Methods More Lecturer’s webpage: Information http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/leccadito/ 21 3rd year Course Code 27003127 Course Name Multivariate Data Analysis ISCED Code CFU (ECTS) 10 Course Year 3rd Year Degree in Statistics for Business and Insurance Semester Winter Lecturer Prof. TARSITANO Agostino Activity Type Teaching Total Hours / 60 / 6 Hours per Week Apprenticeship NO Language of Italian Instruction Course Contents: Exploratory Multivariate Analysis and its pre-processing: Principal Component Analysis, Discriminant Analysis, Cluster Analysis: Hierarchical and non-hierarchical approach. Multiple Linear Regression Model. Recommended Zani S., Analisi dei dati Multidimensionali; vol. 2, Giuffrè Editore. Gherghi M., Lauro or Required C., Appunti di Analisi dei Dati Multidimensionale RCE EDIZIONI, 2004. Bolasco S., Reading Analisi multidimensionale dei dati, Carocci. Fabbris L., Statistica multivariata. Analisi esplorativa dei dati, McGraw-Hill Companies. Mardia K.V., Kent J.T., Bibby J.M., Multivariate Statistical Analysis, Academic Press Inc. Prerequisites basic knowledge of statistics, Statistical Inference, Mathematical Analysis and Linear Algebra. Exam of statistics Teaching Lectures and laboratory Methods Assessment Written and oral Methods More Lecturer’s webpage: Information http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/tarsitano/ 22 Course Code 27000109 Course Name Introduction to Database Systems ISCED Code ING-INF/05 CFU (ECTS) 10 Course Year 3rd Year Degree in Statistics for Business and Insurance Semester Spring Lecturer Prof. GRECO Sergio / MOLINARO Cristian Activity Type Teaching Total Hours / 60 / 6 Hours per Week Apprenticeship NO Language of Italian Instruction Course Contents: Database system concepts and architecture; The relational data model; The relational algebra; The SQL language (Data Definition Language, Data Manipulation Language and Data Query Language); Data modeling using the Entity-Relationship (ER) model; Relational database design by ER-to-relational mapping; Database interactions in application program through libraries of database functions Recommended Lecture notes of the teacher P. Atzeni, S. Ceri, S. Paraboschi, e R. Torlone, Basi di or Required Dati - Modelli e Linguaggi di Interrogazione, McGraw-Hill Libri Italia Reading Prerequisites Exam of foundations of computer science Teaching Front lectures and exercises, self study, homework and practical activities at the Methods Laboratory of Computer Science (LDI) Assessment The examination consists of a practical test (to be held at the Laboratory of Methods Computer Science), a written test and an oral test. More Lecturer’s Page: Information http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/greco/ http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/molinaro/ 23 Course Code 27003078 Course Name Demography ISCED Code CFU (ECTS) 5 Course Year 1st Year Degree in Statistics for Business and Insurance Semester Spring Lecturer Prof. STRANGES Manuela Activity Type Teaching Total Hours / 30 / 6 Hours per Week Apprenticeship NO Language of Italian Instruction Course Contents: Aims and goals of demography. The statistical sources for the demographic analysis: ancient and modern sources, ecclesiastical sources, statistical and administrative sources. Notions and basic tools for analysis: the concepts of time, duration and age, intensity and timing of demographic phenomena; pure measures and measurements in the presence of interference, independence or continuity hypothesis. Analysis of the population structure: age distribution, structure indices, age ratios, sex distribution, sex ratios, the population pyramid. Basic analysis of demographic phenomena: crude rates, specific rates, total rates; relationship between generic and specific rates; Direct and indirect standardization. Elements of longitudinal and transversal analysis: measures for period analysis and cohort analysis; the Lexis diagram and its extensions. Measures of demographic growth: equation of population; arithmetic, geometric and continuous growth measures; natural and migration components of population growth; the logistic model. Mortality: notes on the historical origins and uses of life tables, the life table and its biometric functions; measurements in the presence of interference; functions in the discrete and continuous time; relationship between mortality rates and the probability of death; abbreviated mortality tables; the stationary population; the point of Lexis. Infant mortality: measures (infant mortality rate, perinatal, neonatal, early neonatal, late neonatal rates, etc..); infant mortality by cause; the biometric pattern of Bourgeois-Pichat. Marriage: marriage rates; flow statistics and status, intensity and frequency of marriage; analysis of contemporary marriage, the marriage table, special measures of marriage, dissolution of marriage; basic measurements of the divorce. Fertility: analysis of fertility by generation, period analysis of fertility, intensity and frequency of fertility, general and specific rates, special measures of fertility, legitimate and illegitimate fertility, fertility by birth order, probability to increase fertility. Migration: mobility and migration; intensity and frequency of migration; longitudinal and transversal analysis of migration; special measures (efficiency index, index of differential migration, redistribution). Forecasts and demographic projections: the synthetic method and the analytical or cohort-components method; estimates of births; forecasts with the migratory movement. Models of population: stable population, stationary population. Further topics related to the development of contemporary demography and interrelationships between population, economy and society. Recommended De Santis G., “Demografia”, Serie Manuali, Il Mulino, Bologna, 2010. Stranges M., or Required “Elementi di Demografia e Statistica per il Territorio”, CELUC – Centro Editoriale e Reading Librario, Università della Calabria, Arcavacata di Rende (Cosenza), 2005. De Bartolo G., “Elementi di analisi demografica e demografia applicata”, CELUC – Centro Editoriale e Librario, Università della Calabria, Arcavacata di Rende (Cosenza), 1997. Additional material will be suggested by the teacher during the Prerequisites Teaching Methods Assessment Methods More Information lessons None Lectures + exercises Written examination Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/stranges/ 24 Course Code 27003115 Course Name Actuarial Mathematics ISCED Code CFU (ECTS) 10 Course Year 3rd Year Degree in Statistics for Business and Insurance Semester Winter Lecturer Prof. PIRRA Marco Activity Type Teaching Total Hours / Hours 60 / 6 per Week Apprenticeship NO Language of Italian Instruction Course Contents: Introduction to life insurance. Survival models. Life tables and selection. Premium calculations. Term insurance, Pure endowment, Endowment, Annuities. Policv values. Recommended or “Matematica e Tecnica Attuariale delle assicurazioni sulla durata di vita”, Required Reading Edizioni LINT, Trieste, 2000 Prerequisites Financial Mathematics, Statistics, Statistics and Probability Teaching Methods Lectures Assessment Oral exam Methods More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/pirra/ 25 Course Code Course Name ISCED Code CFU (ECTS) Course Year Semester Lecturer Activity Type Total Hours / Hours per Week Apprenticeship Language of Instruction 27003116 Private and Insurance Law 10 3rd Year Degree in Statistics for Business and Insurance Spring Prof. MAISTO Filippo Teaching 60 / 6 NO Italian Course Contents: PRIVATE LAW: Sources - Principles - Acts - Rules - Interpretation -Contracts – Torts. INSURANCE LAW: Economical operation – Enterprises and Companies – Controls Insurance contracts . Recommended or P. PERLINGIERI, Istituzioni di diritto civile, Edizioni Scientifiche Italiane, Napoli, Required Reading ult. ed., PARTI: I; IV-lett. A; V. - A. DONATI-G. VOLPE PUTZOLU, Manuale di Prerequisites Teaching Methods Assessment Methods More Information diritto delle assicurazioni, Giuffrè, Milano, ult. ed. None Lectures Oral examination Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/maisto/ 26 Course Code 27003117 Course Name Actuarial Techniques of Non-Life Insurance ISCED Code CFU (ECTS) 10 Course Year 3rd Year Degree in Statistics for Business and Insurance Semester Winter Lecturer Prof. CERCHIARA Rocco Roberto Activity Type Teaching Total Hours / 60 / 6 Hours per Week Apprenticeship NO Language of Italian Instruction Course Contents: 1. Introduction – Premium calculation 2. Premium calculation of MTPL insurance 3. Technical Reserves 4. Reinsurance and solvency Recommended - Daykin C., Pentikainen T., Pesonen M. (1994): “Practical Risk Theory for or Required Actuaries”, Ed. Chapman & Hall, Pagg. 1-154; 155-178; 357-363; 397-404 Reading Daboni L. (1993), Lezioni di tecnica attuariale delle assicurazioni contro i danni, LINT, Trieste, pagg. 189- 197 -Klugman S. A. et al. (2008), “Loss Models: from data to decisions”, Third Edition, John Wiley - Nuovo codice delle Assicurazioni (2005) -Useful websites: www.iasb.org; www.actuaires.org; www.ceiops.org Prerequisites None Teaching Lectures and tutorials Methods Assessment Oral exam Methods More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/cerchiara/ 27 Course Code Course Name ISCED Code CFU (ECTS) Course Year Semester Lecturer Activity Type Total Hours / Hours per Week 27003162 Corporate Finance 10 3rd Year Degree in Statistics for Business and Insurance Winter Prof. CARIOLA Alfio / Monteforte Daniele Teaching 60 / 6 Apprenticeship NO Language of Italian Instruction Course Contents: Present Values, the Objectives of the Firm, and Corporate Governance . Why Net Present Value Leads to Better Investment Decisions than Other Criteria. Alternatives to NPV. Introduction to Risk, Return, and the Opportunity Cost of Capital. Payout Policy and Capital Structure Recommended or Required Reading Prerequisites Teaching Methods Assessment Methods More Information Brealey, Myers. Principles of Corporate Finance, McGraw Hill, more recent ed. None Traditional and interactive lectures, cases studies, workout classes, and self-study. Written examination. Oral examination (possible in some cases). Evaluation range: from 18 to 30 cum laude. Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/monteforte/ 28 Course Code 27000023 Course Name Operations Research ISCED Code CFU (ECTS) 10 Course Year 3rd Year Degree in Statistics for Business and Insurance Semester Winter Lecturer Prof. MENZIETTI Massimiliano Activity Type Teaching Total Hours / Hours 60 / 6 per Week Apprenticeship NO Language of Italian Instruction Course Contents: • Introduction to Operations Research. • Mathematical programming models and formulation of some problems. • Linear Programming. Graphic solution. Simplex Method. Two Phase Method. • Theory of duality. Dual problem and complementarity relationships. Dual Simplex Method. Economic interpretation of the dual problem and the dual solution. Sensitivity analysis. • Integer linear programming. Branch and Bound Methods. Cutting Plane Methods. Recommended or • S. Martello, M.G. Speranza , Ricerca Operativa per l’Economia e l’Impresa, Ed. Required Reading Esculapio, 2012 • F.S. Hillier, G.J. Lieberman, Ricerca operativa - Fondamenti, 9/ed, McGraw-Hill, 2010 • C. Vercellis, Ottimizzazione - Teoria, metodi, applicazioni, McGraw-Hill, 2008. • F. Schoen, Modelli di Ottimizzazione per le Decisioni, Ed. Esculapio, Bologna, 2006. • M.S. Bazaraa, J.J. Jarvis, H.D. Sherali, Linear Programming and Network Flows, Wiley, 2005. • A. Sforza, Modelli e metodi della ricerca operativa, 2/ed, Edizioni Scientifiche Italiane, 2005. • Supplementary notes of the teacher Prerequisites Vector spaces, Scalar and Matrix Multiplication, inverse of a matrix, determinant of a matrix, systems of linear equations and inequalities, limits and derivatives, gradient vector and Hessian matrix. Teaching Methods Lectures, home works, group works Assessment Methods Mid-term and final exams More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/paletta/ 29
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