Types of Sampling (Probability & Non-Probability) in Research

This Video explains the steps, examples, advantages and disadvantages of Various Sampling Methods (Probability and non-probability) in Research.
The probability sampling methods mentioned are,
1. simple random sampling,
2. systematic random sampling,
3. stratified random sampling,
4. Cluster sampling
5. Multi-stage sampling
6. Multiphase sampling
The non-probability sampling methods mentioned are,
1. Convenience sampling,
2. Judgement or purposive sampling,
3. Snow Ball sampling,
4. quota sampling.
5. Self-selection sampling
#research
#samplingtechniques
Sampling is an essential aspect of research, as it involves selecting a subset of individuals or items from a larger population for the purpose of making inferences about the whole population. There are two main types of sampling methods in research: probability sampling and non-probability sampling. Each has its advantages and limitations.
Probability Sampling:
Simple Random Sampling: In this method, each member of the population has an equal and independent chance of being selected. This is often achieved using random number generators or drawing lots.
Systematic Sampling: Researchers select every nth member from a list, usually starting with a random member. For instance, if you have a list of 100 people, you might select every 10th person.
Stratified Sampling: The population is divided into subgroups or strata based on certain characteristics (e.g., age, gender), and then random samples are taken from each stratum. This ensures that each subgroup is adequately represented.
Cluster Sampling: The population is divided into clusters (e.g., geographic regions), and then a random sample of clusters is selected. Researchers then collect data from all members of the selected clusters.
Multistage Sampling: This method combines various sampling techniques. It typically involves selecting clusters using cluster sampling and then selecting individuals within those clusters using another sampling method, such as simple random sampling.
Non-Probability Sampling:
Convenience Sampling: Also known as accidental sampling, researchers select the most readily available subjects. This method is quick and easy but may introduce bias.
Judgmental or Purposive Sampling: Researchers use their judgment to select specific individuals or items because they believe they are most relevant to the research. This method is often used in qualitative research.
Snowball Sampling: Used in situations where it is challenging to identify participants. Researchers begin with a small group of known participants and ask them to refer other potential participants.
Quota Sampling: Researchers divide the population into subgroups and select a specific number of individuals from each subgroup, typically based on characteristics of interest.
Volunteer or Self-Selected Sampling: Participants voluntarily choose to be part of the sample. This method is often used in surveys or studies involving self-reporting, but it may introduce bias as those who volunteer may not be representative of the larger population.
Each sampling method has its own advantages and limitations, and the choice of method depends on the research objectives, available resources, and the nature of the population being studied. Probability sampling methods are generally preferred when researchers aim for high representativeness and generalizability, while non-probability methods are often used when probability sampling is not feasible or when certain characteristics of the population are of primary interest.
#SamplingMethods
#ProbabilitySampling
#NonProbabilitySampling
#SimpleRandomSampling
#StratifiedSampling
#ClusterSampling
#SystematicSampling
#MultistageSampling
#ConvenienceSampling
#JudgmentalSampling
#QuotaSampling
#SnowballSampling
#VolunteerSampling
#SamplingTechniques
#SurveySampling
#ResearchSampling
#SamplingBias
#SampleSize
#SamplingErrors
#datacollection
References:
byjus.com/maths/sampling-meth....
www.questionpro.com/blog/type...
www.scribbr.com/methodology/s...
www.ncbi.nlm.nih.gov/pmc/arti...
www.indeed.com/career-advice/...