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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 Sample Survey INSTRUCTOR YONGYUTH CHAIYAPONG Ph.D. (Mathematical Statistics) MANAGER OF THAILAND HEALTH SURVEY OFFICE
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
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
Steps in Conducting a Sample Survey • Planning Stage • Field Operation • Data Processing
Planning Stage • Target Population and Sampled Population • Population Unit • Output Tables • Content • Frame
Planning Stage • Sampling Plan, Sample Select, Sample Allocation • Planning for Field Operation • Planning for Data Processing • Pilot Survey
Field Operation • Data Collection • Quality Control • Manual Editing
Data Processing • Data Entry • Editing and Updating • Tabulation • Validation of Outputs
Fundamental Concepts of Theory of Sample Survey • Population is Finite. • Population does not obey or is “Free” from any probability model.
Population Characteristics • Population Total • Population Mean • Population Proportion • Ratio
Error • Sampling Error • Non-Sampling Error To Achieve Reliable Estimates • Appropriate Sampling Plan • Efficient Estimator
Fundamental Sampling Plans • Simple Random Sampling • Stratified Sampling • Systematic Sampling • Single Stage Cluster Sampling • Two Stage Cluster Sampling
Probabilistic Sampling • Random Sampling of Population Units • A Set of Samples • Probability Model Simple Random Sampling • Sampling without Replacement • Sampling with Replacement
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
Estimation of Population Average and Total • Sample Mean • Number Raised Estimator • Probability Density Function of the Estimator • Unbiasness • Variance
Estimation of Proportion • Sample Proportion • Hypergeometric Distribution • Binomial Distribution • Unbiasness • Variance
Sample size determination • Population variance • Variance of estimator • Error level • Cost of the survey • Estimation in subgroups
Estimation of population characteristics • Sampling plan • Appropriate estimator (unbiased and minimum variance) • Weighting procedure
Sample Survey Errors Non Sampling Error Sampling Error
Survey Methodology • Population and Population Units • Questionnaire Design • Concepts and Definitions • Sampling Plan • Sample Size & Sample Allocation • Frame • Estimation of Population Characteristics • Variance Estimation
SamplingError Sampling Plan Estimator
Data Collection Data Processing Protocol Data Entry Non Sampling Error Measurement Error Definitions
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
Thailand Health Examination Survey III • Systematic sampling • Relationship between structure of the sampling plan and estimation procedure • Ratio Estimator and its advantages