Sampling in Qualitative research

The prevailing strategy of quantitative research method is probability

sampling. It depends on the choice of random and representative sample

from larger population. Probability sampling is used in successive

generalization of the research findings to the population. Contrastingly, in

qualitative research, purposeful sampling is the leading strategy. It

gathers information-rich cases that can be studied in depth (Patton, 1990).

As Mack et al. (2005, p. 3) says, that is not required to collect data from

everyone in a community in order to get correct findings, even if it were

doable. In qualitative research, only a sample (a subset) of a population is

chosen for any given study. The study’s research objectives and the

characteristics of the study population (such as size and diversity)

conclude which and how many people to pick.

I will now succinctly describe three of the most frequent sampling

methods. Which I would be referring to use in qualitative research:

purposive sampling, quota sampling, and snowball sampling.

Purposive sampling

Purposive sampling is one of the most general sampling strategies,

groups’ participants according to preselected criteria related to a specific

research question. Sample sizes, which may or may not be set prior to

data collection, depend on the resources and the available time and also

the study’s objectives. Purposive sample sizes are frequently determined

based on the source of theoretical saturation (the point in data collection

when new data no longer brings more insights to the research questions).

Hence Purposive sampling is most successful when data review and

analysis are done in concurrence with data collection.

According to there are various types of purposive sampling. Those are

typical case sampling, deviant or extreme case sampling and maximum

variation, confirming or disconfirming case sampling, convenience case

sampling, politically important case sampling etc (Patton, 1990).

Quota sampling

Quota sampling, at times considered a type of purposive sampling, is also

usual. While designing the study of how many people with which

characteristics to take in as participants is decided by us in quota

sampling. Individuality might comprise place of residence, age, class,

gender, martial status, profession etc. The criteria that is chosen by us,

permits us to concentrate on people we think would be most likely to

experience, know about, or have insights into the research topic. After

this we go into the community and by means of recruitment strategies

suitable to the location, culture, and study population – get people who

match these criteria, until we meet the agreed quotas.

How do purposive and quota sampling differ?

The common aspect about Purposive and quota sampling is that they both

seek out to classify participants based on selected criteria. However,

quota sampling is more precise with respect to sizes and proportions of

subsamples, with subgroups selected to reflect resultant proportions in the

population. For example, taking gender in consideration, if we try

knowing how people have an perspective about playing golf or watching

the sport, a quota sample would find an equal balance of men and women

in a given city, assuming a 1:1 gender ratio in the population. Studies

utilize purposive rather than quota sampling depending on the number of

participants. When the number of participants is more of a target than a

unfaltering requirement – that is, a fairly accurate rather than a strict

quota.

Snowball sampling

Snowballing is a third type of sampling, it also known as chain referral

sampling. It is taken as a type of purposive sampling. Participants or

informants, who we have already contacted, will refer us to other people

who could have a potential to contribute to our study. Using the Snowball

sampling could help us find and recruit “hidden populations,” that is,

groups that are not easily reachable through other sampling strategies

(Mack, et. al., 2005).

We will most probably use this kind of sampling for our research.

Qualitative sampling assumptions

(Ladner. S, 2008)

Social actors are not conventional like objects. Randomized events

are inappropriate to social life.Probability

sampling is expensive and ineffective. Non-probability

sampling is the finest approach.

Types of Samples

(Ladner. S, 2008)