NON-PROBABILITY SAMPLING Flashcards
methods rely on random selection, ensuring that each member of the population has a known, nonzero chance of being included in the sample. This randomness minimizes bias and allows researchers to generalize findings to
the larger population.
Probability sampling
It is based on the subjective judgment of the researcher rather
than random selection
▪ It is carried out by observation, and researchers use it widely
for qualitative research.
Non-Probability
Sampling
are used when researchers
cannot randomly select participants, often due to logistical
constraints or the nature of the research question. These
methods rely on the researcher’s judgment and specific criteria
to select participants, rather than random chance
Non-probability sampling methods
Is the cornerstone of quantitative
research, where the goal is to make statistically valid inferences
about a population based on the sample data.
Probability sampling
are methods used to select a sample (a subset of a population) for
research. However, they differ significantly in how they
approach participant selection, leading to distinct advantages,
disadvantages, and applications.
Non/
Probability
Sampling
Give me the 16 Types of Non-probability Sampling
Maximum Variation
Sampling
Critical Case
Sampling
Homogenous
Sampling
Theory-Based
Sampling
Confirming and
Disconfirming Cases
Snowball or Chain
Sampling
Extreme or Deviant
Case Sampling
Typical Case
Sampling
Intensity Sampling
Politically Important
Cases
Random Purposeful
Sampling
Stratified Purposeful
Sampling
Criterion Sampling
Opportunistic
Sampling
Combination or
Mixed Sampling
Convenience
Sampling
This technique aims to capture a wide range of
perspectives and experiences by selecting participants
who represent diverse characteristics or viewpoints.
The goal is to maximize the variation within the sample
to gain a comprehensive understanding of the
phenomenon being studied.
Maximum Variation
Sampling
How to employ the maximum variation sampling method?
- Identify key characteristics that contribute to variation in the phenomenon of interest.
- Select participants who represent a wide range of these
characteristics. - Continue selecting participants until you reach a point where new participants are not providing significantly different perspectives
This technique involves selecting cases that are crucial
for understanding a particular phenomenon or theory.
These cases are often considered “typical” or
representative of a larger population
Critical Case
Sampling
How to employ the critical case sampling method?
- Identify cases that are considered critical for understanding the
phenomenon or theory. - Select these cases for in-depth study.
- Ensure that the selected cases are representative of the larger
population or phenomenon.
This method focuses on selecting participants who
share similar characteristics or experiences. It is useful
for in-depth exploration of a specific group or
phenomenon.
Homogenous
Sampling
How to employ Homogenous sampling method?
- Define the specific characteristic or experience that defines the homogenous group.
- Select participants who share this characteristic or experience.
- Ensure that the sample size is sufficient for in-depth analysis
of the shared characteristic or experience
This method involves selecting participants based on
their relevance to a specific theory or framework. The
researcher chooses cases that can either support or
challenge the existing theory
Theory-Based
Sampling
How to employ the Theory-Based
Sampling method?
- Identify the key concepts and propositions of the theory.
- Select participants who represent different aspects of these
concepts and propositions. - Analyze the data to determine how the participants’
experiences support or challenge the theory
This technique involves selecting participants who
either confirm or disconfirm a particular hypothesis or
theory. The researcher seeks to identify cases that
support the hypothesis and cases that contradict it.
Confirming and
Disconfirming Cases