Diapositiva 1 - University of Novi Sad

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Transcript Diapositiva 1 - University of Novi Sad

A proposal for the master programme in
applied statistics:
Statistical Methods for the mesurement of
the quality of services
Biagio Simonetti
Universita' del Sannio (Italy)
Master Programme in Applied Statistics
Novi Sad, December 10 2010
University of Sannio
Benevento, the provincial capital of Samnium
(Sannio), is a very important city for the
Campania region for its history and cultural
patrimony.
Samnium is a green, mountainous area, whore
history has been developing for about 30
centuries with very important events, such as
the defeat of the Romans by the Samnites (321
B.C.), the victory of Rome over Pyrrus (275
B.C.) and the battle between Charles of Anjou
and Manfred (1266).
Benevento, the provincial capital of Samnium,
dates from the 4th century B.C. when it was
known as Maloenton, a name turned into
Beneventum with the Roman colony which
marked the beginning of its greatest splendor
with the Appian Way and the Trajan Way.
There are many archeological records, starting
from the Trajan’s Arch (or Golden Door),
erected in 114 A.D., 15.45 m high and with
8.60 m span, and the Roman Theatre,
built by Adriano and restored by Commodus
in the late 2nd century A.D..
The University of Sannio
(Italian: “Università degli Studi del Sannio”,
UNISANNIO) is located in
Benevento, southern Italy.
It was founded in 1998 and is organized in 4
Faculties (Economic and Business Sciences,
Engineering, Laws, Sciences).
This young University, since its birth, has
considered internationalization as one of its
most qualifying points and feeds, in a
significant way, the exchanges and the
diffusion of the applied research
to the territory.
Students who choose our University can deepen their studies in the fields of
Law, Statistics, Environment, Geology, Biotechnologies, Civil, Computer,
Energy and Telecommunication Engineering, Economics and
Business Organization.
UNIVERSITY of SANNIO
Faculty of Law
Faculty of Sciences
Law
Law and firms
Faculty and
Degree Course A.Y. 2010/2011
Biotechnologies
Biological Sciences
Earth Sciences
Faculty of Economics and Business Sciences
I Cycle
Business Sciences
Tourism Management
Services Management
Security Management
Statistical and Actuarial Sciences
II Cycle
Economics and Governance
Economics and Management
Statistical and Actuarial Sciences
Faculty of Engineering
Civil Engineering
Energetic Engineering
Computer Engineering
Telecommunication Engineering
Statistics and Actuarial Sciences
The aim of the course in Statistics and Actuarial Sciences is to
ensure that the students have an appropriate knowledge of
statistical methods and general principles of other important
subjects. At the same time they must have specific knowledge
about the statistical, probabilistic and actuarial field.
In this way they will be professionists able to use the statistical
tecnhique for the evaluation of private and social insurance
systems and for the analysis of the financial markets.
Statistics and Actuarial Sciences
The course in statistical and actuarial sciences gives an
appropriate preparation, both methodological and
practical, in the statistical field, with specific
competences in financial and insurance sector.
The lessons are generally oriented to the study of problems
pertaining to:
1. the project and realization of statistical survey;
2. the building of models for the forecasting of economic,
demographic, social and business problems;
3. the informatics organization of the data;
4. the control of financial and demographic risks about the
private and public insurance systems in the bank and
financial firm sector.
Organization of Statistics and
Actuarial Sciences
• The Course is organized in 2 cycles. The
basic one and the graduate studies one.
• The first cycle has a duration of 3 years;
• The second one has a duration of 2 years.
The first cycle (First year)
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Mathematics;
Statistics;
Foreign language I;
Foreign language II;
Mathematics for finance;
Juridical notions;
Stochastic processes
The first cycle (Second year)
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Sampling theory;
Statistical inference;
Demography;
Actuarial Mathematic;
Economical statistics;
Actuarial technique for life insurance
The first cycle (Third year)
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Data analysis I;
Data analysis II;
Time series analysis;
Demography II;
Data elaboration;
Financial and actuarial computation;
Statistical methods for firm decision;
Financial markets and institutions
The second cycle (first year)
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Economics and management;
Statistical models for complex data;
Statistical models;
Economy – Advanced course;
Mathematical models for financial markets;
Risk theory
The second cycle (second year)
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Statistical laboratory;
Statistical models – Advanced course;
Statistical inference – Advanced course;
Financial legislation;
Actuarial technique – Advanced course;
Mathematics – Advanced course
Description of some courses
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Statistics
Descriptive statistic and exploratory data analysis. Numerical and qualitative data.
Frequency distributions. Location measures. Variability measures. Inequality
measures. Graphical methods. Skewness. Joint distributions. Chi-squared index of
association. Linear correlation. Rank correlation. Goodman and Kruskal index of
association. Eta square index of association.
Probability. Random experiments and events. Probability postulates and theorems.
Conditional probability and independent events. Bayes theorem. Univariate random
variables. Bivariate random variables. Binomial distribution. Hypergeometric
distribution. Poisson distribution. Geometric distribution. Normal distribution. Uniform
distribution. Exponential distribution. Chi-squared, Student’s t and Fisher’s F
distribution. Convergences of sequence of random variables. Central limit theorem.
Laws of large number and other theorems related to convergences of sequence of
random variables.
Inference. Sampling. Point estimation: properties of estimators and estimation
methods. Sample size. Interval estimation. Hypotheses testing: introduction, tests on
means and proportion, p-value. Chi-squared test for independence. Inference on the
correlation coefficient. Simple linear regression: assumptions, estimation, test on
regression coefficients, R squared, prediction.
Description of some courses
• Time series analysis
Explorative analysis of time series. Component estimation via
mathematical function. Moving averages. Stochastic processes. AR,
MA, ARMA, ARIMA models. Box Jenkins procedure. The prevision in
ARMA model.
• Statistical models
Linear Regression. Multiple linear regression. Ordinary least
squares. Hypothesis test in the regression model. Analysis of
Variance. Model for binary responses. Contingency tables.
• Statistical models - Advanced course
Structural equation models: notation, covariances, Path Analysis.
Introduction to the dependence graph. Graph propriety.
Measurement errors and consequences. Model evaluation.
Description of some courses
• Stochastic processes
Introduction to stochastic processes: definition and mathematical
description, stationary processes, classification of stochastic
processes. Time and ensemble averages, covariance and
autocorrelation functions, a-dependent processes. White noise,
weakly stationary processes, the ergodic process, processes with
stationary and independent increments. Probability generating
function. The branching process, the probability of ultimate
extinction. The random walk, absorbing and reflecting barriers, the
symmetric random walk, the ballot theorem. Markov chains, the
equilibrium probability, the classification of states, ergodic chains,
the mean recurrence time, the first passage probability, the mean
first passage time, the limit theorem for Markov chains, irreducible
chains and equilibrium distributions, limiting properties of irreducible
chains. The Eherenfest’s diffusion model, the Bernoulli-Laplace
model. The Wiener process (Brownian processes), the diffusion
equations for the Wiener processes. The Poisson process, timedependent Poisson process, weighted Poisson process, the
compound Poisson process.
The role of the statistician in Italy
The statistician in Italy has the possibility to work in private
and public firms and in the research institution, as for
example the “ISTAT” (National Institute of Statistics) and
in other statistical services of the public administration.
The role of the statistician is mainly related to activities
that deal with the production, extraction and
management of the knowledge.
Furthermore, it can be employed as a consultant of the
firms (generally medium-small firms) that has not a
statistician in their organization and are not able to
efficiently analyze market information.
The role of the statistician in Italy
The statistician can be employed for:
• the study of social problems related to the different local
reality;
• the analysis of the trend of the population;
• the study of the economics and financial forecast of the
nation;
• the planning of sample surveys;
• epidemiological surveys;
• the analysis of consumer preferences;
• the study of the television audience;
• the political surveys;
• the statistical control of the quality;
• the customer satisfaction analysis
Why this proposal?
The evaluation of the quality of the services is a topic in
continuous evolution;
The private firms and the public institution that offer services
could increase their income and their visibility in the market if
they consider the quality as one of the primary objectives;
For this reason, our research team has built a “Permanent work
group: Statistics for the Evaluation and the Quality of the
Services”; it is an official group of the Statistical Italian Society
and it organized and will organize many events about the quality
services.
So there are the right ability to perform a master on this topic. It
will be interesting for students and for worker of public and
private firm too.
The aim of the group
The group has the aim to promote and coordinate the methodological research
inherent the statistical techniques for the evaluation of the services quality.
One of the goal is to promote the aggregation of people that operate for the
research of statistical instruments useful for the evaluation of the services
quality.
Furthermore it has the aim to promote the international contacts.
It can:
• Promote the diffusion of the news about the scientific activity of the
members;
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Encourage occasions for collaboration between university and private and
public institutions;
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Foster the diffusion of statistical techniques for the evaluation and the
quality of the services;
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Promote activities for the diffusion of the statistical methodology in this field
both to a local level and to an international level.
Some activities organized by the
group
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Evaluation and Customer Satisfaction for the Quality of the services. Rome,
8-9 September 2005;
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Methods, models and Information Technologies for Decisions Support.
Procida, 28-30 September 2006.
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Statistical Methods for the mobility and the evaluation of customer
satisfaction in public transportation system. Pescara, 25 September 2009
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The evaluation of the teaching system by students: collecting data via web.
Rome, 23 June 2010.
Statistical Methods for the Evaluation of the services. Florence, 30 May – 1
June 2011.
Summer School (July 22-26 2011) on Statistical methods for the evaluation
of the quality of services, Nigde University (Turkey)
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Master proposal: Statistical Methods for the
Measurement of the Quality of Services
• The ISO 11098 addresses the key performance indicators of
construction organizations, based on the quality perceived by the
customer / user in order to improve the effectiveness of actions
taken by the organization.
• In this context it is clear the primary role assumed by the use of
statistical methods, which must be aligned with the processing of
data in this type of analysis, appropriate ways to achieve useful
results for management purposes, strictly applied, paying close
attention to all stages of the process.
• The Master “Statistical Methods for the Measurement of the Quality
of Services“ will be presented by professors of Statistics and it will
offer the necessary knowledge to students that want to improve the
competences in the field of the evaluation of the quality of services.
Master proposal: Statistical Methods for the
Measurement of the Quality of Services
• Special emphasis will be given to the use of multivariate
statistical techniques for data analysis, some particularly
innovative.
• Multivariate statistics concerns understanding the
different aims and background of each of the different
forms of multivariate analysis, and how they relate to
each other. The practical implementation of multivariate
statistics to a particular problem may involve several
types of univariate and multivariate analysis in order to
understand the relationships between variables and their
relevance to the actual problem being studied.
The aim of the master
The aim of the master will be the formation of a professional figure that
will be able to evaluate the quality of services offered by public and
private organization, using the classical statistical techniques and
the new one that will be studied deeply during the years.
The master will be addressed to students that are graduated in
Economis, Statistics, Mathematics or in subject that can be
considered equivalent.
Furthermore it can be directed to manager of firm or of public
institutions that can be potentially interested in improving their
knowledge about the evaluation of the quality.