32821 - Survey sampling

Course Unit Page

  • Teacher Elisabetta Carfagna

  • Credits 6

  • SSD SECS-S/01

  • Teaching Mode Traditional lectures

  • Language English

SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Quality education Decent work and economic growth Reduced inequalities

Academic Year 2019/2020

Learning outcomes

By the end of the course the student should know the basic theory of survey sampling. In particular the student should be able: - to employ simple, stratified and probability sampling - to derive the estimators and associated standard errors of population in the different sampling strategies - to correct estimation by the ratio principle - to understand the difference between observational and experimental studies

Course contents

Probability sampling

Simple random sampling

Sampling proportions and percentages

The estimation of sample size

Stratified random sampling

Further aspects of stratified random sampling

Sampling from two frames

Ratio estimators

Regression estimators

Systematic sampling

Area frame sample designs

Single-stage cluster sampling: clusters of equal size

Single-stage cluster sampling: clusters of unequal sizes

Subsampling with units of equal size

 

Double sampling

Sources of errors in surveys

Readings/Bibliography

Cochran W.G. (1977). Sampling Techniques, third edition, Wiley, New York.

Chapters to be studied:

  • Introduction Chapter 1;
  • Simple random sampling Chapter 2;
  • Sampling Proportions and Percentages Chapter 3: from 3.1 to 3.2
  • Estimation of sample size Chapter 4: from 4.1 to 4.4; 4.6 ; 4.8; 4.11
  • Stratified random sampling Chapter 5: from 5.1 to 5.7;
  • Further aspects of stratified sampling Chapter 5A: from 5A.1 to 5A.3; from 5A.9 to 5A.11; 5A.15;
  • Ratio estimators Chapter 6: from 6.1 to 6.4;
  • Regression estimators Chapter 7: from 7.1 to 7.4; 7.6 and 7.10;
  • Systematic sampling Chapter 8: from 8.1 to 8.6; 8.8, 8.13, 8.14;
  • Single stage cluster sampling Chapter 9: from 9.1 to 9.4; 9.6;
  • Single-Stage Cluster Sampling: Clusters of Unequal Size Chapter 9A: from 9A.1 to 9A.3;
  • Subsampling with units of equal size Chapter 10: from 10.1 to 10.4;
  • Double sampling Chapter 12: 12.1; 12.2; 12.4;
  • Sources of error Chapter 13: 13.1.

Teaching methods

Lectures and practicals

Assessment methods

Oral exam made of two parts.

In the first part, exercises have to be solved; in the second part, theoretical questions will be asked. The student has to show to be able to choose and apply the appropriate sampling method and corresponding estimators for solving specific problems.

Office hours

See the website of Elisabetta Carfagna