Credit hours
In-class work per week |
Practice per week |
Credits |
Duration |
Total |
3 |
1 |
8 |
15 weeks |
120 hours |
Instructor
Idemauro Antonio Rodrigues de Lara
Sônia Maria De Stefano Piedade
Objective
Capacitate students in the planning of sample designs as well as in the estimation methods involved.
Content
Module Outline: Probabilistic and non-probabilistic sampling designs, point and interval estimation
methods, applications and computational resources.
Program Content
1. Introduction to sampling problems and mathematical foundation. 2. Simple random sampling with
and without replacement. 3. Systematic sampling. 4. Stratified sampling. 5. Cluster sampling. 6.
Sampling in two or more stages. 7. Ratio and regression estimators. 8. Unequal probability sampling and
sampling in complex designs. 9. Sample and population sizing. 10. The non-response in the analysis. 11.
Non-probabilistic sampling. 12. Bootstrap.
Bibliography
Bolfarine, H. Bussab, W.O. Elementos de Amostragem. São Paulo, SP. Edgard Blücher, 2005.
Cochran, W.G. Sampling Techniques, N.Y. John Wiley, 1977.
Hedayart, A.S.; Sinha, B.K. Design and Inference in Finite Population Sampling. John Wiley, 1991.
Heeringa, S. G., West B. T., Berglund P. A. Applied Survey Data Analysis. Chapman-Hall, 2020.
Lohr, Sharon. Sampling: Design and Analysis. 3rd ed. Chapman-Hall, 2022.
Manly, B.F.J. Statistics for Environmental Science and Management, Chapman-Hall, 2000.
Mendehall, W. Scheaffer, R.L. Ott. L. Elementary Sampling, 6th ed. Southbank: Thomson, 2006.
Valliant, R; Dorfman, A.H; Royall, R.M. Finite Population Sampling and Inference. John Willey, 2000.
Thompson, S.K. Sampling. 3rd. Edition, John Wiley, 2012.