🔴 How to select Participants: Quantitative Research

Dr Tomi Omoya
15 Jul 202207:52

Summary

TLDRIn this video on sampling in quantitative research, the presenter outlines four key sampling methods: Simple Random Sampling, where participants are randomly selected for equal representation; Systematic Sampling, which involves choosing every nth individual from a list; Stratified Sampling, designed to capture various demographic groups within a population; and Clustered Sampling, suitable for large populations by selecting random clusters (e.g., universities). Each method is illustrated with examples, particularly focused on YouTube users, providing viewers with a comprehensive understanding of effective sampling strategies for their research.

Takeaways

  • 😀 Quantitative research focuses on understanding cause-and-effect relationships and measuring variables in a fixed reality.
  • 😀 Sampling is crucial in quantitative research as it helps generalize findings to a larger population.
  • 😀 Simple random sampling ensures every individual in the population has an equal chance of selection.
  • 😀 To implement simple random sampling, researchers must define their population and create a comprehensive list of potential participants.
  • 😀 Systematic sampling involves selecting participants at regular intervals from a numbered list, ensuring representativeness.
  • 😀 Stratified sampling captures various demographic groups by dividing the population into strata based on specific characteristics.
  • 😀 Each stratum in stratified sampling must be represented to ensure a comprehensive understanding of the population.
  • 😀 Cluster sampling is effective for large populations, where entire clusters (e.g., universities) are randomly selected for inclusion.
  • 😀 Using a mix of sampling methods can enhance the reliability and validity of quantitative research findings.
  • 😀 Understanding different sampling techniques helps researchers choose the most suitable method for their specific study needs.

Q & A

  • What is the primary goal of quantitative research?

    -The primary goal of quantitative research is to understand causal relationships and measure variables in a way that allows for generalization of findings.

  • What is simple random sampling?

    -Simple random sampling is a method where participants are randomly selected from a population, giving everyone an equal chance of being included.

  • How can a researcher ensure a sample is representative of the general population?

    -A researcher can ensure a sample is representative by using methods like simple random sampling, which randomizes participant selection, or stratified sampling, which accounts for demographic diversity.

  • What steps are involved in simple random sampling?

    -First, define the population of interest, create a list of potential participants, assign random numbers to them, and then randomly select participants until the desired sample size is reached.

  • What is systematic sampling?

    -Systematic sampling is a method of selecting participants at regular intervals from a numbered list of the population, such as choosing every 10th person.

  • What is the purpose of stratified sampling?

    -Stratified sampling is used to ensure that different demographic groups within a population are represented in the sample, by categorizing participants into strata based on characteristics like age or gender.

  • Can you give an example of how stratified sampling works?

    -If a researcher wants to study YouTube users by age group, they would categorize users into age strata and then sample from each stratum to ensure diverse representation.

  • What is clustered sampling, and when is it most useful?

    -Clustered sampling involves dividing the population into clusters and randomly selecting entire clusters for study. It is most useful when dealing with large and dispersed populations.

  • How does clustered sampling differ from simple random sampling?

    -Clustered sampling selects entire groups (clusters) at once, whereas simple random sampling selects individuals randomly from the entire population.

  • Why is understanding sampling methods important for researchers?

    -Understanding sampling methods is crucial because the choice of sampling technique affects the reliability, validity, and generalizability of research findings.

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Etiquetas Relacionadas
Sampling MethodsQuantitative ResearchResearch TechniquesAcademic InsightsStatistical AnalysisDemographic StudiesResearch DesignData CollectionEducational ContentResearch Tutorials
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