Sampling Theory and Methods
Objectives
· Cover basic theoretical and practical aspects of survey sampling;
· Familiarize participants with sampling terminology and the general objectives of sample surveys;
· Present the classical statistical sampling methods, conditions and situations where each one 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
200184
Credits
7.5
Responsible teacher
Pedro Miguel Pereira Simões Coelho
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 general statistics
- descriptive statistics
- inductive statistics;
- Perfect conceptual master of specific concepts like
- Random Variable
- Distribution
- Parameters
- Estimator
- Estimate
- Estimators’ main properties
- Confidence intervals (relevant)
- Hypothesis testing (optional)
- Central limit Theorem (relevant)
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: S p r i n g e r V e r l a g , I S B N 0 - 3 8 7 - 9 7 5 2 8 - 4 Carl-Erik Särndal, Sixten Lundström (2005)
- Estimation in Surveys with Nonresponse. Chichester: W i l e y , I S B N 0 - 4 7 0 - 0 1 1 3 3 - 5
- Pinheiro J, Coelho, P et all, As Sondagens (2016), Escolar Editora, ISBN 9789725925140.
Teaching method
Theoretical Practical courses based in presentations and a number of variants using very specific excel intereactive files.
Evaluation method
Midterm 35% Final exam 65%
Subject matter
The complete syllabus is in the respective moodle website:
https://elearning.novaims.unl.pt/pluginfile.php/114160/mod_resource/content/0/Syllabus%20Sampling%20Theory%20and%20Methods%20Spring%202022.pdf
Programs
Programs where the course is taught:
- Specialization in Information Analysis and Management
- Specialization in Risk Analysis and Management
- Specialization in Business Intelligence
- Specialization in Data Science for Marketing
- Specialization in Digital Marketing and Analytics
- Specialization in Information Systems
- Specialization in Marketing Intelligence
- Specialization in Marketing Research and CRM
- specialization in Digital Transformation
- Specialization in Business Intelligence – Working Hours
- Laboral - Especialização em Data Science for Marketing
- Specialization in Digital Marketing and Analytics
- specialization in Information Systems - working hours
- Specialization in Marketing Intelligence
- Master Degree in Data Driven Marketing
- PostGraduate in Information Analysis and Management
- PostGraduate Risk Analysis and Management
- PostGraduate in Business Intelligence
- PostGraduate in Data Science for Marketing
- PostGraduate Digital Marketing and Analytics
- PostGraduate Marketing Research e CRM
- PostGraduate in Information Management and Business Intelligence in Healthcare
- PostGraduate Information Systems Management
- PostGraduate in Marketing Intelligence
- PostGraduate in Enterprise Information Systems
- Pós-Graduação em Transformação Digital