Sampling and Surveys

Recommended Prerequisites

Basic course in Probability and Statistics.

Teaching Methods

The classes are essentially of expository style and include examples (using real or simulated data) and exercises to apply the material being taught.

Learning Outcomes

The main goal is studying the theoretical principles that support the main procedures used in statistical inference for finite populations. The student should understand the limitations and advantages of each sampling design and be able to proof the main properties of the corresponding estimators. The student should also know how to use statistical software to deal with simulated or real data and use Monte-Carlo techniques to compare sampling designs.

This course aims to develop the following skills: ability to calculate, knowledge of mathematical results, ability to formulate and solve problems, design or use of mathematical models to real situations.

Work Placement(s)

No

Syllabus

Classical sampling designs: simple random sampling - estimation of totals, means and ratios; stratified sampling; poststratification; cluster sampling; systematic sampling.

Sampling with unequal probabilities: Hansen-Hurvitz and Horvitz-Thompson estimators;probability proportional to size (PPS) and inclusion probabilities proportional to size (IPPS) sampling.

Other topics in sampling (selection depending on time available): optimality and admissibility; nonresponse; two-phase sampling; complex surveys.

Head Lecturer(s)

Carlos Manuel Rebelo Tenreiro da Cruz

Assessment Methods

Assessment
During the semester there are two mid-term exams (75 to 100% of the grade) and a set of homework assignments (until 25% of the grade) given every 2 or 3 other weeks and handed individually. The homework exercises are mathematical problems or short computational tasks. The final exam option consists of an exam (75 to 100% of the grade) and a computational assignment (until 25% of the grade): 100.0%

Bibliography

S.L. Lohr, Sampling: Design and Analysis, Duxbury Press, 1999.

Y. Tillé, Théorie des Sondages: Échantillonnage et Estimation en Populations Finies, Dunod, 2001.

A.S. Hedayat, B.K. Sinha, Design and Inference in Finite Population Sampling, Wiley, 1991.

W.G. Cochran, Sampling Techniques, Wiley, 1977.

S.K. Thompson, Sampling, Wiley, 2002.