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Sample Survey

Sample Survey. Sample Survey. INSTRUCTOR YONGYUTH CHAIYAPONG Ph.D. (Mathematical Statistics) MANAGER OF THAILAND HEALTH SURVEY OFFICE. Type of Population in Statistics Theory. Finite Population Infinite Population. Inference for Infinite Population.

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Sample Survey

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  1. Sample Survey Sample Survey INSTRUCTOR YONGYUTH CHAIYAPONG Ph.D. (Mathematical Statistics) MANAGER OF THAILAND HEALTH SURVEY OFFICE

  2. Type of Populationin Statistics Theory • Finite Population • Infinite Population Inference for Infinite Population • Point and Interval Estimation of Probability Model Parameters • Hypotheses Testing of Probability Model Parameters

  3. Inference for Finite Population • Computation of Population Characteristics (Census) • Estimation of Population Characteristics (Sample Survey) Census VS Sample Survey * Budget and Time * Coverage * Accuracy * Feasibility

  4. Steps in Conducting a Sample Survey • Planning Stage • Field Operation • Data Processing

  5. Planning Stage • Target Population and Sampled Population • Population Unit • Output Tables • Content • Frame

  6. Planning Stage • Sampling Plan, Sample Select, Sample Allocation • Planning for Field Operation • Planning for Data Processing • Pilot Survey

  7. Field Operation • Data Collection • Quality Control • Manual Editing

  8. Data Processing • Data Entry • Editing and Updating • Tabulation • Validation of Outputs

  9. Fundamental Concepts of Theory of Sample Survey • Population is Finite. • Population does not obey or is “Free” from any probability model.

  10. Population Characteristics • Population Total • Population Mean • Population Proportion • Ratio

  11. Error • Sampling Error • Non-Sampling Error To Achieve Reliable Estimates • Appropriate Sampling Plan • Efficient Estimator

  12. Fundamental Sampling Plans • Simple Random Sampling • Stratified Sampling • Systematic Sampling • Single Stage Cluster Sampling • Two Stage Cluster Sampling

  13. Probabilistic Sampling • Random Sampling of Population Units • A Set of Samples • Probability Model Simple Random Sampling • Sampling without Replacement • Sampling with Replacement

  14. Fundamental Concept of SRS • A population unit is randomly selected from the population one at a time until a set of sample of size “n” is achieved • At each of the selection process, the remaining population units have an equal chance of being selected • A set of samples occurs with an equal probability

  15. Estimation of Population Average and Total • Sample Mean • Number Raised Estimator • Probability Density Function of the Estimator • Unbiasness • Variance

  16. Estimation of Proportion • Sample Proportion • Hypergeometric Distribution • Binomial Distribution • Unbiasness • Variance

  17. Sample size determination • Population variance • Variance of estimator • Error level • Cost of the survey • Estimation in subgroups

  18. Estimation of population characteristics • Sampling plan • Appropriate estimator (unbiased and minimum variance) • Weighting procedure

  19. Sample Survey Errors Non Sampling Error Sampling Error

  20. Survey Methodology • Population and Population Units • Questionnaire Design • Concepts and Definitions • Sampling Plan • Sample Size & Sample Allocation • Frame • Estimation of Population Characteristics • Variance Estimation

  21. SamplingError Sampling Plan Estimator

  22. Data Collection Data Processing Protocol Data Entry Non Sampling Error Measurement Error Definitions

  23. Thailand Health Examination Survey III • Stratified three stage clustered sampling • Combination of basic sampling plans • Factor for stratification and rationale • Cluster sampling or sub-sampling

  24. Thailand Health Examination Survey III • Systematic sampling • Relationship between structure of the sampling plan and estimation procedure • Ratio Estimator and its advantages

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