Introduction to Survey Sampling U.S. Census Bureau, Washington, D.C

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Introduction to Survey Sampling U.S. Census Bureau, Washington, D.C. This workshop will present the main components of survey sampling, with a focus on probability sampling. Participants will learn some basic probability sampling techniques such as simple random sampling, systematic sampling, stratification, cluster sampling, and multistage sampling. Participants will also learn about producing estimates of population parameters from sample surveys as a function of sample design and weighting procedures. Finally, participants will learn to compute the sampling errors of survey estimates, and to make inferences from them to the population. The workshop focuses on sample survey methodologies and principles, but participants are encouraged to bring any census or survey questions that are relevant to their job responsibilities. The workshop is conducted in a hands-on and interactive environment. In addition, all participants must bring a calculator that includes at least a square root function in order to complete group exercises outside the workshop setting. Audience and Prerequisites This introductory workshop is oriented toward statisticians, demographers, and economists who wish to produce or understand probability sampling procedures such as sample design, statistical estimates, and variance estimators. No previous experience in probability sampling is required although experience using mathematics, statistics, and computer languages is desirable. Participants should not expect to obtain sufficient background in this workshop to master probability sampling, but they can expect to become familiar with basic techniques well enough to converse with sampling statisticians more easily about sample design and estimation. Date: December 2 - 13, 2019 Place: U.S. Census Bureau Headquarters Suitland, Maryland (near Washington, D.C.) Tuition: US $3,000 Apply early. The workshop will be limited to 15 participants. Those who complete the application requirements will be accepted on a first-come, first-served basis. For more information e-mail [email protected]. .

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CHAPTER IV CHOOSING THE SAMPLE This chapter is written for survey coordinators and technical resource persons. It will enable you to: U Understand the basic concepts of sampling. U Calculate the required sample size for national and subnational estimates. U Determine the number of clusters to be used. U Choose a sampling scheme. UNDERSTANDING THE BASIC CONCEPTS OF SAMPLING In the context of multiple-indicator surveys, sampling is a process for selecting respondents from a population. In our case, the respondents will usually be the mothers, or caretakers, of children in each household visited,1 who will answer all of the questions in the Child Health modules. The Water and Sanitation and Salt Iodization modules refer to the whole household and may be answered by any adult. Questions in these modules are asked even where there are no children under the age of 15 years. In principle, our survey could cover all households in the population. If all mothers being interviewed could provide perfect answers, we could measure all indicators with complete accuracy. However, interviewing all mothers would be time-consuming, expensive and wasteful. It is therefore necessary to interview a sample of these women to obtain estimates of the actual indicators. The difference between the estimate and the actual indicator is called sampling error. Sampling errors are caused by the fact that a sample&and not the entire population&is surveyed. Sampling error can be minimized by taking certain precautions: 3 Choose your sample of respondents in an unbiased way. 3 Select a large enough sample for your estimates to be precise.
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