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Sampling Strategies and Data Collection is a core component of research that outlines how to select a representative group from a larger population and the methods used to gather information from them
Learning Objectives
- Explain Core Sampling Concepts: Explain the fundamental concepts of sampling, including the distinction between a population and a sample, and the primary goal of selecting a representative sample to allow for generalization
- Describe Probability Sampling Techniques: Describe the major probability sampling techniques (Simple Random, Systematic, Stratified, Cluster) and explain why their use of random selection is the gold standard for making statistical inferences about a population
- Describe Non-Probability Sampling Techniques: Describe the major non-probability sampling techniques (Convenience, Purposive, Quota, Snowball) and identify the specific research situations where these methods are most appropriate, despite their limitations for generalizability
- Identify Factors for Determining Sample Size: Identify the key factors that influence sample size determination, including practical constraints (budget, time) and statistical concepts (power, effect size, variability)
- Evaluate Modes of Survey Administration: Evaluate the primary modes of survey administration (online, mail, telephone, face-to-face), comparing their respective strengths and weaknesses regarding cost, speed, coverage, and potential for bias