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
How to employ the confirming and disconfirming cases?
- Formulate a hypothesis or theory.
- Select participants who represent both confirming and
disconfirming cases of the hypothesis or theory. - Analyze the data to determine the extent to which the
participants’ experiences support or contradict the hypothesis or theory.
How to employ the snowball or chain sampling?
- Identify a few initial participants who meet the study criteria.
- Ask these participants to refer other individuals who also meet
the criteria. - Continue this process until the desired sample size is reached.
This technique involves selecting participants who
represent extreme or unusual cases of the
phenomenon being studied. These cases can provide
valuable insights into the boundaries or limits of a
phenomenon.
Extreme or deviant case sampling
This method involves starting with a small group of
participants and then asking them to refer other
individuals who fit the study criteria. It is useful for
reaching hard-to-reach populations or those with
specific characteristics.
Snowball or Chain
Sampling
How to employ the method of extreme or deviant case sampling?
- Identify the extreme or deviant cases of the phenomenon of
interest. - Select these cases for in-depth study.
- Analyze the data to understand the unique characteristics and
experiences of these extreme cases.
This method involves selecting participants who
represent the average or typical case of the
phenomenon being studied. It is useful for gaining a
general understanding of a phenomenon
Typical Case
Sampling
How to employ typical sampling method?
- Define the characteristics of a typical case of the phenomenon.
- Select participants who exhibit these characteristics.
- Analyze the data to understand the common experiences and
perspectives of typical cases
This method involves selecting participants who are
considered influential or important in a particular
political context. These cases can provide insights into
the dynamics of power and influence in a particular
setting.
Politically Important
Cases
This technique involves selecting participants randomly
from a specific population that is relevant to the
research question. It is a combination of random
sampling and purposeful sampling
Random Purposeful
Sampling
