Marketing Research Sampling Methods
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Questions and Answers

What is the main characteristic of probability sampling?

Each member of the population has a known, non-zero probability of being selected.

What is the primary difference between probability and nonprobability sampling?

Random selection of participants versus non-random selection or convenience-based selection.

What type of sampling involves dividing the population into subgroups and randomly selecting from each subgroup?

Stratified Sampling.

What type of nonprobability sampling involves selecting participants based on predetermined quotas?

<p>Quota Sampling.</p> Signup and view all the answers

What type of sampling involves selecting every nth member of the population?

<p>Systematic Sampling.</p> Signup and view all the answers

What is the primary advantage of cluster sampling over other probability sampling methods?

<p>It can be more cost-effective.</p> Signup and view all the answers

What is the main difference between quota sampling and stratified sampling?

<p>Quota sampling is a non-probability sampling method, whereas stratified sampling is a probability sampling method.</p> Signup and view all the answers

What is the purpose of setting quotas in quota sampling?

<p>To ensure that the sample is representative of the population in terms of key characteristics.</p> Signup and view all the answers

What is the main characteristic of stratified sampling?

<p>It involves dividing the population into subgroups (strata) based on key characteristics.</p> Signup and view all the answers

What is the key difference between probability sampling and non-probability sampling?

<p>Probability sampling involves random selection, whereas non-probability sampling does not.</p> Signup and view all the answers

Study Notes

Sampling in Marketing Research

Types of Sampling

Probability Sampling
  • Involves random selection of participants from the population
  • Each member of the population has a known, non-zero probability of being selected
  • Allows for generalization of results to the population
  • Examples:
    • Simple Random Sampling: each member of the population has an equal chance of being selected
    • Systematic Sampling: selecting every nth member of the population
    • Stratified Sampling: dividing the population into subgroups and randomly selecting from each subgroup
Nonprobability Sampling
  • Does not involve random selection of participants
  • Sampling is based on convenience, judgment, or other non-random criteria
  • Results may not be generalizable to the population
  • Examples:
    • Convenience Sampling: selecting participants based on ease of access
    • Judgment Sampling: selecting participants based on expert judgment
    • Snowball Sampling: selecting participants through referrals from existing participants

Quota Sampling

  • A type of nonprobability sampling
  • Involves selecting participants based on predetermined quotas (e.g. age, gender, occupation)
  • Ensures that the sample is representative of the population in terms of key characteristics
  • Quotas are often set based on demographic data or previous research

Stratified Sampling

  • A type of probability sampling
  • Involves dividing the population into subgroups (strata) based on key characteristics
  • Randomly selecting participants from each stratum
  • Ensures that the sample is representative of the population in terms of key characteristics
  • Examples:
    • Stratifying by age, income, and occupation to study consumer behavior

Cluster Sampling

  • A type of probability sampling
  • Involves dividing the population into clusters (e.g. geographic areas, organizations)
  • Randomly selecting clusters and then selecting participants from each cluster
  • Can be more cost-effective than other probability sampling methods
  • Examples:
    • Selecting a random sample of cities and then surveying residents within each city

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Description

Test your knowledge of sampling techniques in marketing research, including probability and non-probability methods, quota sampling, stratified sampling, and cluster sampling. Learn how to select participants and ensure representative samples.

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