APPLIED STATISTICS 1

APPLIED STATISTICS 1

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iten
Code
52508
ACADEMIC YEAR
2018/2019
CREDITS
6 credits during the 2nd year of 8766 Mathematical Statistics and Data Management (L-35) GENOVA
SCIENTIFIC DISCIPLINARY SECTOR
SECS-S/01
LANGUAGE
Italian
TEACHING LOCATION
GENOVA (Mathematical Statistics and Data Management)
semester
2° Semester
Teaching materials

OVERVIEW

Three important areas of Statistics are introduced: sampling theory, time series and official statistics. The first part deals with theoretical and practical elements of the design, analysis and inference of survey data obtained by probabilistic sampling. The second part develops the main aspects of the theory and practice of the analysis of time series in the time-domain and hints to the analysis in the frequency domain. The third part introduces and motivates by examples the principle and structure of official Statistics in Italy.

AIMS AND CONTENT

LEARNING OUTCOMES

To introduce some statistical techniques and their specific applications.

AIMS AND LEARNING OUTCOMES

At the end of the course students will be able to

  • judge the validity of a sample survey
  • plan and analyze simple sample surveys also by aid of software
  • evaluate mathematical properties of a probabilistic sample
  • develop further knowledge about the theory and practice of statistical sampling
  • present a report with the analysis of a sample and a critique of its design

At the end of the course students will

  • be able to perform the analysis of simple time series in the time domain also with software
  • be able to develop further theoretical and computational knowledge for statistical analysis of time series
  • be able to present a simple report about the statistical analysis of a time series
  • possess the essential mathematical and statistical knowledge related to time series

At the end of the course students will

  • be able to obtain official data on the Italian population from the SISTAN webnet 
  • have developed an understanding of the guiding principle of official statistics and of the European code of Statistics

Teaching methods

Combination of traditionals lectures and lab sessions with the software R.

SYLLABUS/CONTENT

Statistical sampling from a finite population. Simple random sampling with and without replacement. Stratified sampling. Proportional allocation and optimal allocation. Statistical estimators of means and their variances.

Time series: exploratory analysis. The notions of stationarity and ergodicity. Strong and weak stationary processes. Autocovariance function and partial autocovariance function. SARIMA models.

Official Statistics: Public statistics, data sources, the official data, the SISTAN system, main Italian regulations on official statistics, code of practice. 

RECOMMENDED READING/BIBLIOGRAPHY

Campionamento
1. Vic Barnett Sample Survey, Principle and methods, Third Edition, John Wiley & Sons, Ltd, 2002.
2. William Cochran, Sampling Techniques, John Wiley & Sons, 1977.
3. Sharon L. Lohr, Sampling: Design and Analysis. Second Edition, Brooks/Cole, 2010.
4. Dispense di Daniela Cocchi (in rete).
5. Formulario ed alcuni esercizi su aulaweb (al sito del corso, in file) oppure http://www.dima.unige.it/ rogantin/StatInd/index.htm
6. Giuseppe Cicchitelli, Amato Herzel, Giorgio Eduardo Montanari, Il campionamento statistico, Il Mulino, 1997. Fisica 519.24 CIC 30.
7. Luigi Fabbris, Lindagine campionaria: metodi, disegni e tecniche di campionamento, Carocci, 1989. Economia 519.52/002 MA-ST, Scienze della formazione VI/a.779, e in altre biblioteche di unige. 

Serie storiche
1. C. Chatfield (1980). The analysis of Time Series: an introduction, Chapman and Hall.
2. D. Piccolo C. Vitale (1981) Metodi statistici per l'analisi economica, Il Mulino

 Dispense/Handouts

TEACHERS AND EXAM BOARD

Ricevimento: By appointment arranged by email with Luca Oneto luca.oneto@unige.it and Fabrizio Malfanti <fabrizio.malfanti@intelligrate.it> For organizational issues contact by email Eva Riccomagno <riccomagno@dima.unige.it>  

Exam Board

EVA RICCOMAGNO (President)

MARIA PIERA ROGANTIN (President)

VERONICA UMANITA'

LESSONS

Teaching methods

Combination of traditionals lectures and lab sessions with the software R.

LESSONS START

The class will start according to the academic calendar.

EXAMS

Exam description

Written exam with multiple choice and open questions. Two group projects on topics agreed with the teachers. Discussion of the reports and written test.

Assessment methods

Main points of evaluation are the level of acquisition of the learning objectives and the ability to communicate in a written report the data analyzes carried out during the course.

Exam schedule

Date Time Location Type Notes
05/09/2019 09:00 GENOVA Scritto + Orale

FURTHER INFORMATION

Prerequisites: Statistical Inference in parallel.
Teaching material is available on aulaweb.