In non-probability sampling (also known as non-random sampling) not all members of the population have a chance to participate in the study. In other words, this method is based on non-random selection criteria. This is contrary to probability sampling, where each member
of the population has a known, non-zero chance of being selected to participate in the study. Necessity for non-probability sampling can be explained in a way that for some studies it is not feasible to draw a random probability-based sample of the population due to time and/or cost considerations. In these cases, sample group members have to be selected on the basis of accessibility or personal judgment of the researcher. Therefore, the majority of non-probability sampling techniques
include an element of subjective judgement. Non-probability sampling is the most helpful for exploratory stages of studies such as a pilot survey. The issue of sample size in non-probability sampling is rather ambiguous and needs to reflect a wide range of research-specific factors in each case. Nevertheless, there are some considerations about the minimum sample sizes in non-probability sampling as illustrated in the table below: Sizes of non-probability sampling[1] The following is the list of the most popular non-probability sampling methods and their brief descriptions: Non-probability sampling methods My e-book, The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step approach contains a
detailed, yet simple explanation of sampling methods. The e-book explains all stages of the research process starting from the selection of the research area to writing personal reflection. Important elements of dissertations such as research philosophy, research approach, research design, methods of data collection and data analysis are explained in this e-book in simple words. John DudovskiyNature of study
Minimum sample size
Semi-structured, in-depth interviews
5 – 25
Ethnographic
35 – 36
Grounded theory
20 – 35
Considering a homogeneous population
4 – 12
Considering a heterogeneous population
12 – 30
Non-probability sampling method
Description
Judgement Sampling (Purposive Sampling)
Researcher chooses samples purely on the basis of her knowledge and credibility
Quota sampling
Researcher chooses sample group members on the basis of their shared traits or characteristics
Convenience sampling
Researcher chooses population members that are conveniently available to her.
Voluntary response sampling
Respondents voluntarily choose to participate in a study, usually through an online survey
Snowball sampling
Initially chosen sample group members help researcher to find new members
Consecutive sampling
Researcher selects a sample or group and after data collection and analysis moves to another sample
Advantages of Non-Probability Sampling
Disadvantages of Non-Probability Sampling
[1] Source: Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6th edition, Pearson Education Limited
Which of the following sampling procedures will be appropriate for conducting researches with empirico-inductive research paradigm?
- Simple random sampling procedure
- Systematic sampling procedure
- Stratified sampling procedure
- Any of the non-probability sampling procedures
Answer (Detailed Solution Below)
Option 4 : Any of the non-probability sampling procedures
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To be able to generalize the research findings of a study to the wider population, we select a sample, so that we can generalize our findings from the sample for the population. The concept of sampling involves selecting a portion (sample) from a bigger group (the sampling population).
Types of Sampling in Research:
- Random/Probability Sampling: In this type, each element in the population has an equal and independent chance of selection in the sample. Types of probability sampling include simple random sampling, stratified random sampling, cluster sampling, etc.
- Non-random/Non-probability Sampling: If the goal is not to generalize to a population but obtain insights into a phenomenon, individual or an event, such as in the case of qualitative research, then a non-probability sampling is used. Types of non-random/non-probability sampling methods include accidental sampling, purposive sampling, snowball sampling, etc.
Empirico-inductive Approach/Paradigm:
- In this paradigm, the researcher collects initial observations and consequently derive a theory that explains those observations. This process can lead to a revision of an old theory or the construction of a new one.
- It begins with a social problem and attempts empirically to induce concepts and causal theories as the study progresses.
- It involves the search for patterns from observation and the development of explanations, theories for those patterns through a series of hypotheses.
- In other words, they move from data to theory or from the specific to the general. This type of research approach has been termed as the “grounded theory” approach.
- It is based on the assumption that the investigator wants to discover, understand and gain insight and therefore must select a sample from which the most must be learned, any of the non-probability sampling methods.
NOTE:
Hypothetico-deductive: In this paradigm, the researchers devise hypotheses based on their existing theory and then design a research strategy to test the hypotheses. It explores a known theory or phenomenon and tests if that theory is valid in given circumstances. A certain theory is replaced if it contradicts a different theory which is better.
Hence, it is clear that any of the non-probability sampling procedures will be appropriate for conducting researches with empirical-inductive research paradigm.
Last updated on Nov 10, 2022
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