Degree Course in Statistics for Business and Insurance ... · Statistics for Business and Insurance...

Degree Course in

Statistics for Business and Insurance

Table of Contents

Degree Course in Statistics for Business and Insurance 2 Courses, Lecturers, Semesters 4 Courses Content 6

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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.

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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.

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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°

DEMOGRAPHY Characterising Statistics, Applied

Statistics, Demographic

SECS-S/04 5 Borrowed from

Demography (0746) 4°

BUSINESS ECONOMICS Characterising Economics and

Business SECS-P/07 10 FABBRINI Giuseppe 1°-2°

PRINCIPLES OF ECONOMICS

Characterising Economics and

Business SECS-P/01 10 RICOTTA Fernanda 3° - 4°

INTRODUCTION TO STATISTICAL COMPUTING 1

Other activities Informatics and telematics skills

SECS-S/01 2 TARSITANO

Agostino 4°

ENGLISH LANGUAGE LABORATORY

Other activities Foreign language L-LIN/12 5

Borrowed from English Language, Economics Degree

Course (0744)

1° - 2°

STATISTICS Basic Statistics and Probabilistic

SECS-S/01 10 LATORRE Giovanni 1° - 2°

II year (enrolled in 2013/2014)




MATHEMATICAL ANALYSIS AND LINEAR

ALGEBRA Basic Mathematics MAT/05 9

PIETRAMALA Paolamaria

1° - 2°

FUNDAMENTALS OF COMPUTER SCIENCE

Basic Informatics ING-INF/05 10 RUSSO Wilma 3° - 4°

STATISTICAL INFERENCE

Basic Statistics and Probabilistic

SECS-S/01 10 COSSARI Antony 3° - 4°

INTRODUCTION TO STATISTICAL COMPUTING 2

Other activities Informatics and telematics skills


Agostino 2°

FINANCIAL MATHEMATICS

Basic Mathematics SECS-S/06 10 COSTABILE

Massimo 1° -2°

STATISTICS FOR BUSINESSES

(curriculum Administration and Analysis of Data)

Characterising Statistics, Applied



Agostino 3° - 4°

ECONOMIC STATISTICS

(curriculum Statistics, Finance and Insurance)



SECS-S/01 10

Borrowed from Statistics for Firms

and Insurance Degree (0746)

3° - 4°

STATISTICS AND PROBABILITY

Composed in coordinated modules:

a) STATISTICS AND PROBABILITY (5 ECTS) b) PROBABILISTIC METHODS FOR ECONOMICS (5 ECTS)

Characterising

Basic

Statistics, Applied Statistics,

Demographic

Mathematics

SECS-S/01

SECS-S/06 10

LECCADITO Arturo COSSARI Antony

1° - 2°

III year (enrolled in 2012/2013)




MULTIVARIATE DATA ANALYSIS


Statistics, SECS-S/01 10

TARSITANO Agostino

1° - 2°

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/pietramala/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/fabbrini/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/ricotta/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/tarsitano/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/latorre/


http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/russo/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/cossari/


http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/costabile/


http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/leccadito/



5

Demographic

INTRODUCTION TO DATABASE SYSTEMS

Characterising Informatics and

Applied Mathematics

ING-INF/05 10

GRECO Sergio MOLINARO

Cristian 3° - 4°

DEMOGRAPHY Characterising Statistics, Applied


SECS-S/04 5 STRANGES

Manuela 4°

ACTUARIAL MATHEMATICS

Refining Refining and integrating activities

SECS-S/06 10 PIRRA Marco 1°- 2°

PRIVATE AND INSURANCE LAW

(group A) Refining

Refining and integrating activities

IUS/01 10 MAISTO Filippo 3° - 4°

ACTUARIAL TECHNIQUES OF NON-

LIFE INSURANCE

(group A)

Characterising Informatics and

Applied Mathematics

SECS-P/06 10 CERCHIARA

Rocco 1° - 2°

CORPORATE FINANCE (group B)

Refining Refining and integrating activities

SECS-P/09 10

Borrowed from Business Finance,

Business Economics Degree

Course (0749)

1°- 2°

OPERATIONS RESEARCH

(group B) Basic

Informatics and Applied

Mathematics MAT/09 10

PALETTA Giuseppe

1° -2°

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/greco/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/molinaro/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/stranges/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/pirra/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/maisto/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/cerchiara/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/paletta/

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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 / Hours per Week

60 / 6

Apprenticeship NO

Language of Instruction

Italian

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 Required Reading

Bertsch-Dal Passo: Elementi di Analisi Matematica, Aracne Editrice. Marcellini-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 Methods

Lectures, tutorials

Assessment Methods

Written and oral

More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/pietramala/


7


Course Name Demography

ISCED Code

CFU (ECTS) 5


Semester Spring

Lecturer Prof. STRANGES Manuela



30 / 6

Apprenticeship NO


Italian

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.


De Santis G., “Demografia”, Serie Manuali, Il Mulino, Bologna, 2010. Stranges M.,

“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

lessons

Prerequisites none

Teaching Methods lectures + exercises

Assessment Methods

written examination

More Information Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/stranges/


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Course Name Business Economics

ISCED Code

CFU (ECTS) 10


Semester Winter

Lecturer Prof. FABBRINI Giuseppe



60 / 6

Apprenticeship NO


Italian

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).


G. Fabbrini – A. Montrone (a cura di), ECONOMIA AZIENDALE – I FONDAMENTI

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/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/fabbrini/

9


Course Name Principles of Economics

ISCED Code

CFU (ECTS) 10


Semester Spring

Lecturer Prof. RICOTTA Fernanda



60 / 6

Apprenticeship 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.


Microeconomics part: Robert S. Pindyck, Daniel L. Rubinfeld, Microeconomia

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

and exercises.

More Information Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/ricotta/

http://www.ecostat.unical.it/ricotta/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/ricotta/

10


Course Name Introduction to Statistical Computing

ISCED Code

CFU (ECTS) 2


Semester Spring

Lecturer Prof. TARSITANO Agostino



12 / 2

Apprenticeship NO


Italian

Course Contents: Applications of explorative statistics statistical, graphical methods, simple simulations, models of random variables


Iacus S. M., Masarotto G. (2008) "Laboratorio di Statistica con R". McGraw-Hill , 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 Methods

Intermediate and final computer test of the type pass/fail

More Information Other optional Teaching Units: Introductory probability Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/tarsitano/


11


Course Name English

ISCED Code

CFU (ECTS) 5


Semester Winter

Lecturer Prof.


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.


Language Leader (Pre-intermediate) Pearson/Longman

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:

12


Course Name Statistics

ISCED Code

CFU (ECTS) 10


Semester Spring

Lecturer Prof. LATORRE Giovanni



60 / 6

Apprenticeship NO


Italian

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


Agresti A., Franklin C. (2009) “Statistics. The Art and Science of Learning from 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 Methods

Written and oral

More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/latorre/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/latorre/

13

2nd year


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



54 + 6 / 6

Apprenticeship NO


Italian

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.


Bertsch-Dal Passo: Elementi di Analisi Matematica, Aracne Editrice. Chirita-Ciarletta: Calcolo, Zanichelli Editore. Bramanti-Pagani-Salsa: Matematica, Calcolo 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 Methods

Lectures and tutorials

Assessment Methods

Written and oral

More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/pietramala/


14


Course Name FUNDAMENTALS OF COMPUTER SCIENCE

ISCED Code ING-INF/05

CFU (ECTS) 10


Semester Spring

Lecturer Prof. RUSSO Wilma



60 / 6

Apprenticeship 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; single-

dimensional and multi-dimensional arrays; input/output operations. Object-oriented programming in

Java: classes, objects, encapsulation, inheritance and polymorphism.


Lecture notes of the teacher; Bertacca, Guidi, Introduzione a Java, McGraw-Hill, 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 Methods

The examination consists of a practical test (to be held at the Laboratory of Computer Science) and an oral test.

More Information Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/russo/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/russo/

15


Course Name Statistical Inference

ISCED Code

CFU (ECTS) 10


Semester Spring

Lecturer Prof. COSSARI Anthony



60 / 6

Apprenticeship 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


- Cicchitelli G., Probabilità e statistica, II edizione, Maggioli Editore (2001) -

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

Written and oral exam

More Information Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/cossari/


16


Course Name Introduction to Statistical Computing 2

ISCED Code

CFU (ECTS) 2


Semester Winter




18 / 2

Apprenticeship NO


Italian

Course Contents: practical applications of some of the most recurrent packages; elements of programming in the R environment.


Iacus S. M., Masarotto G. (2008) "Laboratorio di Statistica con R". McGraw-Hill , 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 Methods

intermediate and final computer test of the type pass/fail

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/


17


Course Name Financial Mathematics

ISCED Code

CFU (ECTS) 10


Semester Winter

Lecturer Prof. MENZIETTI Massimiliano



60 / 6

Apprenticeship NO


Italian

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.


Moriconi F., De Felice M., La teoria dell’immunizzazione finanziaria, Il Mulino, 1991 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 Methods

Self-study, lectures and exercises

Assessment Methods

Written and oral examination

More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/menzietti/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/menzietti/

18


Course Name Statistics for Businesses

ISCED Code

CFU (ECTS) 10


Semester Spring




60 / 6

Apprenticeship NO


Italian

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


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 Methods

Written and oral

More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/tarsitano/


19


Course Name Economic Statistics

ISCED Code

CFU (ECTS) 10


Semester Spring




60 / 6

Apprenticeship NO


Italian

Course Contents:


Prerequisites Exam of Statistics

Teaching Methods Lectures and laboratory

Assessment Methods

Written and oral

More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/tarsitano/


20

INTEGRATED SUBJECT


Course Name Statistics and Probability

ISCED Code

CFU (ECTS) 10


Semester Spring

Prerequisites none

Assessment Methods written and oral exam

MODULE


Course Name Statistics and Probability

ISCED Code

CFU (ECTS) 5


Semester Spring

Lecturer Prof. COSSARI Anthony



30 / 6

Apprenticeship NO


Italian

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.


- Cicchitelli G., Probabilità e statistica, II edizione, Maggioli Editore (2001) - Mood A.M., Graybill F.A., Boes D.C., Introduzione alla statistica, McGraw-Hill Italia (1988) - Slides of the talks.

Prerequisites None

Teaching Methods

30 hours of front lectures

Assessment Methods


More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/cossari/


21

MODULE


Course Name Probabilistic Methods for Economics

ISCED Code

CFU (ECTS) 5


Semester Spring

Lecturer Prof. LECCADITO Arturo



30 / 6

Apprenticeship NO


Italian

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


-Weiss Neil A., Calcolo delle probabilità – Published by Pearson Education, 2008 (English Version: Weiss Neil A., A Course in Probability – Published by Addison-Wesley, 2006 -Lecture Notes

Prerequisites None

Teaching Methods

Frontal lecture

Assessment Methods


More Information

Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/leccadito/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/leccadito/

22

3rd year


Course Name Multivariate Data Analysis

ISCED Code

CFU (ECTS) 10

Course Year 3rd Year Degree in Statistics for Business and Insurance

Semester Winter




60 / 6

Apprenticeship NO


Italian

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.


Zani S., Analisi dei dati Multidimensionali; vol. 2, Giuffrè Editore. Gherghi M., Lauro C., Appunti di Analisi dei Dati Multidimensionale RCE EDIZIONI, 2004. Bolasco S., 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 Methods

Lectures and laboratory

Assessment Methods

Written and oral

More Information

Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/tarsitano/


23


Course Name Introduction to Database Systems

ISCED Code ING-INF/05

CFU (ECTS) 10


Semester Spring

Lecturer Prof. GRECO Sergio / MOLINARO Cristian



60 / 6

Apprenticeship NO


Italian

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


Lecture notes of the teacher P. Atzeni, S. Ceri, S. Paraboschi, e R. Torlone, Basi di

Dati - Modelli e Linguaggi di Interrogazione, McGraw-Hill Libri Italia

Prerequisites Exam of foundations of computer science

Teaching Methods

Front lectures and exercises, self study, homework and practical activities at the Laboratory of Computer Science (LDI)

Assessment Methods

The examination consists of a practical test (to be held at the Laboratory of Computer Science), a written test and an oral test.

More Information

Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/greco/ http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/molinaro/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/greco/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/molinaro/

24


Course Name Demography

ISCED Code

CFU (ECTS) 5


Semester Spring

Lecturer Prof. STRANGES Manuela



30 / 6

Apprenticeship NO


Italian

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.


De Santis G., “Demografia”, Serie Manuali, Il Mulino, Bologna, 2010. Stranges M.,

“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

lessons

Prerequisites None

Teaching Methods

Lectures + exercises

Assessment Methods

Written examination

More Information Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/stranges/


25


Course Name Actuarial Mathematics

ISCED Code

CFU (ECTS) 10


Semester Winter

Lecturer Prof. PIRRA Marco



60 / 6

Apprenticeship NO


Italian

Course Contents: Introduction to life insurance. Survival models. Life tables and selection. Premium calculations. Term insurance, Pure endowment, Endowment, Annuities. Policv values.


“Matematica e Tecnica Attuariale delle assicurazioni sulla durata di vita”, Edizioni LINT, Trieste, 2000

Prerequisites Financial Mathematics, Statistics, Statistics and Probability


Assessment Methods

Oral exam

More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/pirra/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/pirra/

26


Course Name Private and Insurance Law

ISCED Code

CFU (ECTS) 10


Semester Spring

Lecturer Prof. MAISTO Filippo



60 / 6

Apprenticeship NO


Italian

Course Contents: PRIVATE LAW: Sources - Principles - Acts - Rules - Interpretation -Contracts – Torts. INSURANCE LAW: Economical operation – Enterprises and Companies – Controls - Insurance contracts .


P. PERLINGIERI, Istituzioni di diritto civile, Edizioni Scientifiche Italiane, Napoli,

ult. ed., PARTI: I; IV-lett. A; V. - A. DONATI-G. VOLPE PUTZOLU, Manuale di

diritto delle assicurazioni, Giuffrè, Milano, ult. ed.

Prerequisites None


Assessment Methods

Oral examination

More Information Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/maisto/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/maisto/

27


Course Name Actuarial Techniques of Non-Life Insurance

ISCED Code

CFU (ECTS) 10


Semester Winter

Lecturer Prof. CERCHIARA Rocco Roberto



60 / 6

Apprenticeship NO


Italian

Course Contents: 1. Introduction – Premium calculation 2. Premium calculation of MTPL insurance 3. Technical Reserves 4. Reinsurance and solvency


- Daykin C., Pentikainen T., Pesonen M. (1994): “Practical Risk Theory for Actuaries”, Ed. Chapman & Hall, Pagg. 1-154; 155-178; 357-363; 397-404 - 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 Methods

Lectures and tutorials

Assessment Methods

Oral exam

More Information Lecturer’s webpage: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/cerchiara/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/cerchiara/

28


Course Name Corporate Finance

ISCED Code

CFU (ECTS) 10


Semester Winter

Lecturer Prof. CARIOLA Alfio / Monteforte Daniele



60 / 6

Apprenticeship NO


Italian

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


Brealey, Myers. Principles of Corporate Finance, McGraw Hill, more recent ed.

Prerequisites None

Teaching Methods

Traditional and interactive lectures, cases studies, workout classes, and self-study.

Assessment Methods

Written examination. Oral examination (possible in some cases). Evaluation range: from 18 to 30 cum laude.

More Information

Lecturer’s Page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/monteforte/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/esterni/monteforte/

29


Course Name Operations Research

ISCED Code

CFU (ECTS) 10


Semester Winter

Lecturer Prof. MENZIETTI Massimiliano



60 / 6

Apprenticeship NO


Italian

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.


• S. Martello, M.G. Speranza , Ricerca Operativa per l’Economia e l’Impresa, Ed. 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/

http://www.unical.it/portale/strutture/dipartimenti_240/disesf/servizi/paletta/

Degree Course in Statistics for Business and Insurance ... · Statistics for Business and Insurance...

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