The aim of this course is to introduce the main concepts of sample survey theory, emphasising the particular nature of randomness and the importance of precise calculations and presenting the most common survey designs. The role of auxiliary information will be underlined, in both the sampling phase and estimation. The course will be illustrated with examples of surveys, and the survey procedures in SAS will be presented briefly.



  1. General remarks on surveys– Survey basics. The concepts of estimation and precision. Different types of error: sampling error, measurement error, non-response.
  2. Simple random sampling –Estimating a mean, an average, a proportion. Calculation and estimation of precision. Determining the sample size. Estimating a ratio. Domain estimation.
  3. Unequal probability sampling– Estimating a total, a mean, precision. Choosing the probabilities of selection, case of selection with probabilities proportional to the size.
  4. Stratification –Estimation, precision. Sample allocation between the strata: optimal allocation, proportional allocation etc. Constitution of strata: choice of strata variables, choice of the number of strata etc.
  5. Multi-stage sample surveys– Cluster sampling: estimating a total, precision. Case of a simple random sample of clusters. Comparison with the simple random sample. Cluster size. The effect of clusters. Two-stage sampling: estimating a total, precision. Case of a simple random sample at each stage. Comparison with the simple random sample. Self-weighting sample surveys.
  6. Empirical surveys– The quota method (principles, "bias", "precision"). Route sampling. The standard units method. Volunteering.
  7. Estimation by ratio, post-stratification– Definitions, properties, comparison with the simple random sample.
  8. Regression estimation, calibration– Estimation as a residual. Regression estimation: definition, property. Overview of calibration methods.
  9. Correcting non-response– Overview of methods for processing total non-response (reweighting methods) and methods for processing partial non-response (imputation methods).



  • Ardilly P. (2006) : Les techniques de sondage, Technip, Paris.
  • Sarndal C.E., Swenson B., Wretman J. (2003): Model assisted survey sampling, Springer.
  • Tillé Y. (2011) : Sampling Algorithms, Springer.