There are two main methods of sampling. Probability sampling
and Non-probability sampling. Probability sampling methods.
Probability sampling means that every members of the population has a chance of being selected Such chance is known as probability. It is mainly used in quantitative research. There are four main types of probability sampling.
1.Simple Random Sampling.
In a simple random sampling, every member of the population han an equal chance of being selected. The sampling frame should include the whole population.
Example: In an organization of 500 employees the HR team decades on conducting team building activities, it is highly likely that they would prefer picking chits out of a bowl in this case, each of the 500 employees has un equal opportunity of being selected.
2. Systematic Sampling.
Systematic sampling is similar to simple random sampling, but t is usually alightly easier to conduct Every members of the pupulation is listed with a number, but instead of randomly generating numbers, individuals are chosen at regular intervals
Example: All employees of the company are listed in alphabetical order, From the first to 10 numbers, randomly select a starting paint number 6 From number 6 onwards, every 10th person on the list is selected (6,16,26,36, and so on) and end up with a sample of 100 people
3.Stratified Sampling.
Stratified sampling involves dividing the population into subpopulation that may differ in important ways it allows draw mure precise conclusions by ensuring that every subgroup is properly represented in the sample
To use this sampling method divide the population into subgroups called strata) based on the relevant characteristics (eg: gender, age range job, income). Based on the overal proportions of the population, calculate how many people should be sampled from each subgroup. Then use random or systematic sampling to select a sample from each subgroup.
Example: The company has 800 female employees and 200 male employeen You want to ensure that the sample reflects the gender balance of the company, so you sort the population into two straza based on gender. Then use the random sampling on each group, selecting 80 women and 20 men. Which given a representative sample of 100 people
4. Cluster Sampling.
Cluster sampling is a probability sampling technique where the researchers divide the population into multiple groupe clusters) for research Researchers then select random group with simple random or systematic random simpling techniques for data collection and data analysis.
Example: The company has offices in 10 mes across the
country (all with roughly the same number of employees in
similar roles). You don't have the capusity to travel to every office
to collect the dutas, su use random sampling to select 3 offices.
These are the clusters.
Non-Probability Sampling Methods
In a non-probability sample individuals are selected based on non random criteria, and not every individual has a chance of being included. Non-Probability samping techniques are often used in exploratory and qualitative research, the aim is not to tent a hypothesis about a broad population but to develop an initial understanding of a small or under researched population. There are four main types of non probability sampling
1.Convenience or Accidental Sampling.
The sampling means selecting whatever sampling units are conveniently available
Example: interviewing people whome we happen to meet. This sampling may be used for simple purpose such as treating ideas or rough impression about a subject of interst.
2. Judgement Sampling
This type of sampling, also known as purposive sampling, involves the researchers using their expertise to select a sample that is most useful to the purpose of the research
Example you want to know more about the opinions and
experience of disabled students at your university, so you purposefully select a number of students with different support needs in order to gather & vaned range of data on their experiences with student sevices
3.Quota Sampling
Quota sampling method is a non-probability sampling and it can be defined as a sampling method of gathering representative data from a group. Application of quota rampling ensures that sample group represents of the population chosen by the researchers
Example: On the basis of income groups, each interviewer is then
asked to interview a certain number of persons, who constitutes.
4.Snowball Sampling
If the population is hard to access, snowball samping can be used to recrut participants via other participants. The number of people you have access to snowball" as you get in contact with more people.
Example: You are researching experiences of homelessness in your city. Since there is no at of all homicus pecplein the city. probability isn't possible. You meet one person agrees to participate in the research, and she puts you in contact with other homless people that she knows in that area.
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