CODE 108582 ACADEMIC YEAR 2022/2023 CREDITS 6 cfu anno 2 STATISTICA MATEM. E TRATTAM. INFORMATICO DEI DATI 8766 (L-35) - GENOVA SCIENTIFIC DISCIPLINARY SECTOR MAT/06 TEACHING LOCATION GENOVA SEMESTER 2° Semester TEACHING MATERIALS AULAWEB OVERVIEW Two important areas of Statistics are introduced: sampling theory and time series analysis. 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. AIMS AND CONTENT LEARNING OUTCOMES Basic understanding of applications of probability theory for two important statistical techniques, including 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 PREREQUISITES Combination of traditionals lectures and lab sessions with the software R. 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. RECOMMENDED READING/BIBLIOGRAPHY Sampling theory 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. Formulario ed alcuni esercizi su aulaweb (al sito del corso, in file) oppure http://www.dima.unige.it/ rogantin/StatInd/index.htm Time series 1.C. Chatfield (1980). The analysis of Time Series: an introduction, Chapman and Hall 2. Rob J Hyndman and George Athanasopoulos (2nd edition). Forecasting: Principles and Practice, Monash University, Australia https://otexts.com/fpp2/ 3. R.D. Pend e F. Dominici (2008). Statistical methods for environmental epidemiology with R. A case study in air pollution and Health, Wiley 4. R.H. Shumway e D.S. Stoer (2000). Time series analysis and its applications with examples in R, Springer TEACHERS AND EXAM BOARD FRANCESCO PORRO EVA RICCOMAGNO Ricevimento: By appointment arranged by email <riccomagno@dima.unige.it> Exam Board FRANCESCO PORRO (President) SARA SOMMARIVA EVA RICCOMAGNO (President Substitute) LESSONS LESSONS START According to the academic calendar. Class schedule The timetable for this course is available here: Portale EasyAcademy 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 Data appello Orario Luogo Degree type Note 26/06/2023 09:00 GENOVA Scritto 24/07/2023 09:00 GENOVA Scritto 20/09/2023 09:00 GENOVA Scritto FURTHER INFORMATION Students with DSA, disability or other special educational needs are recommended to contact the teacher at the beginning of the course, in order to organize teaching and assessment, taking in account both the class aims and the student's needs and providing suitable compensatory instruments. OpenBadge PRO3 - Soft skills - Sociale base 1 - A PRO3 - Soft skills - Imparare a imparare base 1 - A PRO3 - Soft skills - Creazione progettuale base 1 - A PRO3 - Soft skills - Alfabetica base 1 - A