Sampling Methods in Research

Introduction

• Purpose of the video: Explain the concept of sampling and different types used in research.
• Key terminology:
  • Population: The entire group from which a sample is drawn.
  • Sample: A subset of the population selected to represent the population in research.

Importance of Sampling

• Conducting research on an entire population is often impossible—sampling allows representation with fewer resources.
• Sampling reduces cost and workload, making studies more feasible and efficient.

Types of Sampling

Probability Sampling

• Basis: Every member of the population has an equal chance of being selected.
• Types:
  1. Simple Random Sampling
     • Every member has an equal chance of selection.
     • Eliminates selection bias.
  2. Systematic Sampling
     • Selects the first element randomly, then every nth element.
     • Different from simple random sampling as not every possible sample has an equal chance.
  3. Cluster Sampling
     • Divides the population into clusters, then randomly selects whole clusters.
     • Clusters are internally heterogeneous but externally homogeneous.
  4. Stratified Sampling
     • Divides population into strata (groups) based on characteristics like age, gender, etc.
     • Randomly selects samples from each stratum.
     • Difference from cluster sampling: Includes elements from each stratum rather than whole clusters.

Non-Probability Sampling

• Basis: Not every individual has a known or equal chance of being included.
• Types:
  1. Convenience Sampling
     • Selects individuals who are most accessible.
     • Easy and inexpensive but may not be representative.
  2. Snowball Sampling
     • Existing participants refer new participants.
     • Useful for hard-to-reach populations.
  3. Quota Sampling
     • Ensures sample is proportional to specific characteristics of the population.
     • Common in market research (e.g., quotas based on gender, age).
  4. Purposive (or Judgmental) Sampling
     • Researcher selects samples based on judgment and experience.
     • Often used in qualitative research.

Summary

• Sampling methods can be broadly categorized into probability and non-probability sampling.
• Choosing the appropriate method is crucial for the validity and reliability of the study.
• Probability sampling is generally more robust, but non-probability methods can be useful in specific contexts.

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