Data analysis
A.A. 2018/2019
Obiettivi formativi
Graduate students, researchers in the public and private sector, heads of departments and managers are increasingly dealing with surveys.
This course is intended as an introduction at master/graduate level for those who are new to survey. The aim of the course is to provide an overview of basic probability sampling and estimation methods.
After the course, participants are ready to apply the learned surveys and are able to critically assess existing surveys and survey documentation
This course is intended as an introduction at master/graduate level for those who are new to survey. The aim of the course is to provide an overview of basic probability sampling and estimation methods.
After the course, participants are ready to apply the learned surveys and are able to critically assess existing surveys and survey documentation
Risultati apprendimento attesi
Non definiti
Periodo: Primo trimestre
Modalità di valutazione: Esame
Giudizio di valutazione: voto verbalizzato in trentesimi
Corso singolo
Questo insegnamento non può essere seguito come corso singolo. Puoi trovare gli insegnamenti disponibili consultando il catalogo corsi singoli.
Programma e organizzazione didattica
Edizione unica
Responsabile
Periodo
Primo trimestre
STUDENTI FREQUENTANTI
Programma
Basic concepts in Probability and Statistics: definition of Bernoulli and Normal random variables; point estimation of a mean and a proportion; definition of unbiasedness; definition of variance and mean square error; interval estimation.
The central concept of probability sampling.
The simple random sampling procedure (estimating the mean, the population total and the proportion; variance and standard error of the estimates; confidence intervals and the choice of sample size).
Random sampling with replacement method (estimating the mean, the population total and the proportion; the variance of the estimates; the standard errors; confidence intervals and the choice of sample size).
Non equal probability selection methods (Horvitz-Thompson estimator and Hansen-Hurvitz estimator; variance and standard error of the estimates)
Stratified simple random sampling (estimating the mean, the population total and the proportion; variance and standard error of the estimates; confidence intervals ; optimum choice of stratum sample sizes).
Cluster sampling (estimating the mean, the population total and the proportion; the variance of the estimates; the standard errors; confidence intervals).
Systematic sampling (as a form of cluster sampling).
The central concept of probability sampling.
The simple random sampling procedure (estimating the mean, the population total and the proportion; variance and standard error of the estimates; confidence intervals and the choice of sample size).
Random sampling with replacement method (estimating the mean, the population total and the proportion; the variance of the estimates; the standard errors; confidence intervals and the choice of sample size).
Non equal probability selection methods (Horvitz-Thompson estimator and Hansen-Hurvitz estimator; variance and standard error of the estimates)
Stratified simple random sampling (estimating the mean, the population total and the proportion; variance and standard error of the estimates; confidence intervals ; optimum choice of stratum sample sizes).
Cluster sampling (estimating the mean, the population total and the proportion; the variance of the estimates; the standard errors; confidence intervals).
Systematic sampling (as a form of cluster sampling).
Informazioni sul programma
The first part of the course is devoted to cope the concepts in probability and statistics which are useful to understand the rest of the course. For this part the following book is suggested:
Introductory statistics; Sheldon M. Ross, Ed. Accademic Press: Chapters 1, 2, 3 (Seccions: 3.1, 3.2, 3.5, 3.6), 4 (except Seccion 4.6), 5 (Seccions: 5.1, 5.2, 5.3, 5.4), 6.
For the core of the course, concerning the probability sampling methods, some lecture notes written by the Professor are available on the web site of the course; this material is enough in order to understand the subject and to pass the exam.
Only for students with a background in statistics, if they are interested in studying this topic more in depth, a reference book is:
Sample survey: principles and methods; Vic Barnett, Ed. Arnod (London), 2002: Chapters 1, 2, 4, 5.
Introductory statistics; Sheldon M. Ross, Ed. Accademic Press: Chapters 1, 2, 3 (Seccions: 3.1, 3.2, 3.5, 3.6), 4 (except Seccion 4.6), 5 (Seccions: 5.1, 5.2, 5.3, 5.4), 6.
For the core of the course, concerning the probability sampling methods, some lecture notes written by the Professor are available on the web site of the course; this material is enough in order to understand the subject and to pass the exam.
Only for students with a background in statistics, if they are interested in studying this topic more in depth, a reference book is:
Sample survey: principles and methods; Vic Barnett, Ed. Arnod (London), 2002: Chapters 1, 2, 4, 5.
Propedeuticità
No previous knowledge about statistics is necessary. The first part of the course is devoted to cope the concepts of probability and statistics which are necessary to understand the rest of the course.
Prerequisiti
No previous knowledge about statistics is necessary to follow this course. The first part of the course is devoted to cope the concepts in statistics which are useful to understand the rest of the course, concerning the probability sampling methods.
The exam is written and lasts 1 hour and half. It consists in 3 exercices and 5 multiple choice questions. During the exam students can use books and notes of any kind, because Professor's aim is to test if a student knows when a specific sampling method has to be used. Formulas to be applied can be copied.
Some lecture notes written by the Professor are available on the web site of the course (ARIEL). A reference book is also suggested but it is a bit difficult for students without any background in statistics (the comprehension of this book is not necessary for passing the exam; the lecture notes are enough).
The exam is written and lasts 1 hour and half. It consists in 3 exercices and 5 multiple choice questions. During the exam students can use books and notes of any kind, because Professor's aim is to test if a student knows when a specific sampling method has to be used. Formulas to be applied can be copied.
Some lecture notes written by the Professor are available on the web site of the course (ARIEL). A reference book is also suggested but it is a bit difficult for students without any background in statistics (the comprehension of this book is not necessary for passing the exam; the lecture notes are enough).
Metodi didattici
During lectures, Professor presents a problem and then describes how to solve it by using the more adequate sampling scheme and the corresponding estimator.
Professor explains writing everything on the white-board, usually she does not present slides.
Professor explains writing everything on the white-board, usually she does not present slides.
Materiale di riferimento
STUDENTI NON FREQUENTANTI
Introductory statistics; Sheldon M. Ross, Ed. Accademic Press: Chapters 1, 2, 3 (Seccions: 3.1, 3.2, 3.5, 3.6), 4 (except Seccion 4.6), 5 (Seccions: 5.1, 5.2, 5.3, 5.4), 6.
Lecture notes available on the web site of the course ( or Sample survey: principles and methods; Vic Barnett, Ed. Arnod (London), 2002: Chapters 1, 2, 4, 5).
Lecture notes available on the web site of the course ( or Sample survey: principles and methods; Vic Barnett, Ed. Arnod (London), 2002: Chapters 1, 2, 4, 5).
Programma
Basic concepts in Probability and Statistics: definition of Bernoulli and Normal random variables; point estimation of a mean and a proportion; definition of unbiasedness; definition of variance and mean square error; interval estimation.
The central concept of probability sampling.
The simple random sampling procedure (estimating the mean, the population total and the proportion; variance and standard error of the estimates; confidence intervals and the choice of sample size).
Random sampling with replacement method (estimating the mean, the population total and the proportion; the variance of the estimates; the standard errors; confidence intervals and the choice of sample size).
Non equal probability selection methods (Horvitz-Thompson estimator and Hansen-Hurvitz estimator; variance and standard error of the estimates)
Stratified simple random sampling (estimating the mean, the population total and the proportion; variance and standard error of the estimates; confidence intervals ; optimum choice of stratum sample sizes).
Cluster sampling (estimating the mean, the population total and the proportion; the variance of the estimates; the standard errors; confidence intervals).
Systematic sampling (as a form of cluster sampling).
The central concept of probability sampling.
The simple random sampling procedure (estimating the mean, the population total and the proportion; variance and standard error of the estimates; confidence intervals and the choice of sample size).
Random sampling with replacement method (estimating the mean, the population total and the proportion; the variance of the estimates; the standard errors; confidence intervals and the choice of sample size).
Non equal probability selection methods (Horvitz-Thompson estimator and Hansen-Hurvitz estimator; variance and standard error of the estimates)
Stratified simple random sampling (estimating the mean, the population total and the proportion; variance and standard error of the estimates; confidence intervals ; optimum choice of stratum sample sizes).
Cluster sampling (estimating the mean, the population total and the proportion; the variance of the estimates; the standard errors; confidence intervals).
Systematic sampling (as a form of cluster sampling).
Prerequisiti
No previous knowledge about statistics is necessary to follow this course. The first part of the course is devoted to cope the concepts in statistics which are useful to understand the rest of the course, concerning the probability sampling methods.
The exam is written and lasts 1 hour and half. It consists in 3 exercices and 5 multiple choice questions. During the exam students can use books and notes of any kind, because Professor's aim is to test if a student knows when a specific sampling method has to be used. Formulas to be applied can be copied.
Some lecture notes written by the Professor are available on the web site of the course (ARIEL). A reference book is also suggested but it is a bit difficult for students without any background in statistics (the comprehension of this book is not necessary for passing the exam; the lecture notes are enough).
The exam is written and lasts 1 hour and half. It consists in 3 exercices and 5 multiple choice questions. During the exam students can use books and notes of any kind, because Professor's aim is to test if a student knows when a specific sampling method has to be used. Formulas to be applied can be copied.
Some lecture notes written by the Professor are available on the web site of the course (ARIEL). A reference book is also suggested but it is a bit difficult for students without any background in statistics (the comprehension of this book is not necessary for passing the exam; the lecture notes are enough).
Materiale di riferimento
Introductory statistics; Sheldon M. Ross, Ed. Accademic Press: Chapters 1, 2, 3 (Seccions: 3.1, 3.2, 3.5, 3.6), 4 (except Seccion 4.6), 5 (Seccions: 5.1, 5.2, 5.3, 5.4), 6.
Lecture notes available on the web site of the course ( or Sample survey: principles and methods; Vic Barnett, Ed. Arnod (London), 2002: Chapters 1, 2, 4, 5).
Lecture notes available on the web site of the course ( or Sample survey: principles and methods; Vic Barnett, Ed. Arnod (London), 2002: Chapters 1, 2, 4, 5).
Docente/i
Ricevimento:
Mercoledì dalle 9:00 alle 12:00 (controllare la bacheca su ARIEL per eventuali cambiamenti).
Ufficio n.35, III piano di via Conservatorio