Sampling and Estimation

Objectives

  • To cover basic theoretical and practical aspects of survey sampling
  • Familiarize participants with sampling terminology and the general objectives of sample surveys
  • Presenting the classical  Statistical sampling methods, conditions and situations where each is appropriate
  • Provide practice in applying the sampling methods discussed in class and the calculations of sample dimensions, desired estimates and their measures of precision
  • Be able to apply new knowledge in a daily work environment

General characterization

Code

400015

Credits

6.0

Responsible teacher

José António de Almeida Pinheiro

Hours

Weekly - Available soon

Total - Available soon

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English

Prerequisites

Perfect knowledge of descriptive statistics and inductive statistics.

?On September 15, 2018, Saturday, from 14 to 18 PM an extra course covering the essentials of statistics from the perspective of Sampling and Estimation will be held.

The course is optional but the subjects cannot be revisited during the classes.

This course is designed to put at same level students' statistical knowledge, given their diverse backgrounds.

Bibliography

  • William G. Cochran (1977) Sampling Techniques, 3-rd Ed. New York: Wiley, ISBN 0-471-16240-X
  • Carl-Erik Särndal, Bengt Swensson, Jan Wretman (1992) Model Assisted Survey Sampling. New York: Springer Verlag, ISBN 0-387-97528-4
  • Carl-Erik Särndal, Sixten Lundström (2005) Estimation in Surveys with Nonresponse. Chichester: Wiley, ISBN 0-470-01133-5
  • Pinheiro J, Coelho, P et all, As Sondagens (2016), Escolar Editora, ISBN  9789725925140.

Teaching method

Theoretical and practical courses in EN.

 

Evaluation method

Midterm test and final exam.

Subject matter

·     General framework, notation and terminology

·     Simple random sampling

·     Stratified random sampling

·     Cluster sampling

·     Two-stage sampling

·     Estimation of a ratio

·     Use of auxiliary information

·     Estimation in domains