My Content
Select sampling frame
Choose sampling technique
Determine sampling size
Collect data
Assess response rate
Sampling
A sample is defined as a smaller set of data that a researcher chooses or selects from a larger population by using a pre-defined selection method. These element are known a sample points, sampling units, or observation. Creating a sample is an efficient method of conducting research. In most cases, it is impossible or costly and time-consuming to research the whole population. Hence, examining the sample provides insights that the researcher can apply to the entire population.
Process of Sampling
1. Clearly define target population
2. Select sampling frame
3. Choose sampling technique
4. Determine sampling size
5. Collect data
6. Assess response rate
1. Clearly Define Target Population
The first stage in the sampling process is to clearly difine target population. Population is comenonly related to the number of people living in a particular country.
2. Select Sampling Frame
A Sampling frame is a list of the actual cases from which sample will be drawn. The sampling frame must be representative of the population.
3. Choose Sampling Technique or method
Prior to examining the various types of sampling method, it is worth noting what is meant by sampling, along with reasons why researchers are likely to select a sample.
Taking a subset from chosen sampling frame or entire population is called sampling.
Sampling can be used to make inference about a population or to make generalization in relation to existing theory.
4. Determine Sample Size
In order to generalize from a random sample and avoid sampling errors or biases, a randon sample needs to be of adequate size, what is adequate depends on several issues which often confuse people doing surveys for the first time.
This is because what is important here is not the proportion of the research population that gets sampled, but the absolute size of the sample selected relative to the complexity of the population, the aims of the research and the kinds of statistical manipulation that will be used in data analysis.
5. Collect Data
Once target population, sampling frame, sampling technique and sample size have been established, the next step is to collect data.
6. Assess Response Rate
Response rate is the number of cases agreeing to take part in the study. There cases are taken from original sample. In reality, most researchers never achieve a 100 Percent response rate.
Reasons for this might include refusal to respond, ineligibility to respond, inability to respond, or the respondent has been located but researchers are unables to make content.
In sum, response rate is important because each non response is liable to bias the final sample.
Clearly defining sample, employing the right sampling technique and generating a large sample, in some respects can help to reduce the likelihood of sample bias.
Sampling Types / Sampling Methods
Sampling Methods
A. Probability Sampling Method ( Random ) B. Non-Probability Sampling Method ( Non-Random)
1. Simple Random Sampling i. Convenience Sampling
2. Stratified Sampling ii. Judgmental or Purposive Sampling
3. Cluster Sampling iii. Snowball Sampling
4. Systematic Sampling iv. Quota Sampling
A. Probability Sampling (Equal chance)
Probability sampling to a sampling technique in which sample from a largar population are chosen using a method based on the theory of probability.
This sampling method considers every member of the population and forms samples on the basis of a fixed process.
For example, in a population of 1000 members, each of there members will have 1/100 chances of being selected to be a part of a sample. It gets rid of bias in the population and gives a faire chance to all members to be included in the sample.
1. Sample Random Sampling ( Homogeneous )
One of the best probability sampling techniques that helps in saving time and resources, is the simple random sampling method.
It is a trustworthy method of obtaining information where every single member of a population is chosen randomly, merely by chance and each individual has the exact. Same probability of being chosen to be a part of a sample.
For example, in an organization of 500 employes. if the HR team decided 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 employes has an equal opportunity of being selected.
Like - Lottery Method
2. Stratified Rondom sampling ( Heterogeneous )
Stratified sampling is where the population is divided into strata (on subgroups) and a random simple is taken from each subgroup.
A subgroup is a natural set of items.
subgroups might be based on company size, gender or occupation (to name but a few). stratified sampling is often used where there is a great deal of variation within a population. Its purpose is to ensure that every stratum is adequately represented.
3. Cluster Sampling ()
Cluster sampling is a method where the researcher divide the entire population into sections or cluster that represent a population.
Clusters are identified and included in a sample on the basis of defining demographic parameters such as age, location, sex etc. Which makes it extremely easy for a survey creator to derive effective inference from the feedback.
Naturally accruing group.
Different with Stratified Rondom sampling Cluster Sampling
4. Systematic Sampling
Using systematic sampling method, member's of a sample are chosen at regular intervals of a population.
It requires selection of a starting point for the sample and sample size that can be repeated at regular intervals.
This type of sampling method has а predefined interval and hence this sampling technique is the least time consuming.
For example, a researcher intends to collect a systematic sample of 500 people in a population of 5000. Each element of the population will be mumbered from 1-5000 and every 10 th individual will be chosen to be a part of the sample.
B. Non- Probability Sampling (Not equal chance)
Non-Probability sampling is dfined as a sampling technique in which the researcher selects samples based on the subjective judgement of the researcher rather than random selection.
This sampling method depends heavily on the expertise of the researchers.
It is carried out by observation and researcher use it widely in qualitative researcher.
* higher margin of error, loaded with biases.
a. Convenience Sampling
Convenience sampling is a Non-Probability sampling technique where samples are selected from the population only because they are conveniently available to the researcher.
Researchers choose these samples just because hey are easy to recruit, and the researcher did not consider selecting a sample that represents the entire population.
* Easily accessible of Researcher.
b. Judgement sampling
In the Judgement sampling method, researchers selects the samples based purely on the researcher's knowledge and credibility.
In other words, researchers choose only those people who they deem fit to participate in the research study.
Judgement or purposive sampling is not a scientific method of sampling, and the downside to this sampling technique is that the preconceived notions of a researcher can influence the results.
Thus, this research technique involves a high amount of ambiguity.
c. Quota sampling
Quota sampling is a Non-Probability sampling technique where in the assembled sample has the same proportions of individuals as the entire population with respect to known characteristics, traits or focused phenomenon.
Fixed number of person researcher decided on different category.
d. Snowball Sampling / Chain System
Snowball sampling helps researchers find a sample when they are difficult to locate.
Researchers use this technique when the sample size is small and not easily available.
This sampling system works like the referral program.
Once the researchers find suitable subjects he asks them for assistance to seek similar subjects to from o considerably good size sample.
Accidental Sampling
It is similar to quota sampling, but it is used in market research ( in market places ). Where a researcher can come across any person and they may not have any information.
* No any pre-structed.
Notes :
* The sample size for any research study depends upon four (4p)p
1. Purpose - The required precision of study.
2. Population - The size and nature of population under study.
3. Procedure - The time, budget of the studies.
4. Publishing - The inportance of the study.
Question :
No comments:
Post a Comment