Sampling - An Overview
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Abstract
This document provides an in-depth overview of key sampling concepts and techniques used in population studies. It defines fundamental terms such as population, sample, sampling unit, and sampling frame, along with methods for selecting representative samples, including simple random sampling, stratified sampling, systematic sampling, and cluster sampling. Detailed discussions cover sample size calculation, including factors affecting sample size feasibility and desirability, and the steps involved in conducting 30-cluster sampling, with guidelines for choosing sampling intervals, starting points, and selecting households. Practical examples and formulas are provided to guide researchers in achieving desired precision and confidence levels in sampling.
Description
This resource is designed for researchers and students studying population and sampling methods. It covers foundational sampling concepts, including various sampling techniques, sample size calculation, and application of cluster sampling in field surveys. The document also includes computational steps, exercises, and guidelines for determining sample size for different types of surveys, with an emphasis on practical sampling scenarios and stepwise processes for 30-cluster surveys commonly used in health and demographic research.
Keywords
Sampling, Population Studies, Sampling Methods, Cluster Sampling, Sampling Frame, Random Sample, Sample Size, Sample Calculation, Statistical Confidence, Cluster Survey