Why do you think there is a need to know the sampling procedure and the sample?

Sampling Procedures

There are many sampling procedures that have been developed to ensure that a sample adequately represents the target population. A few of the most common are described below.

Simple Random Sampling
In simple random sampling, every individual in the target population has an equal chance of being part of the sample. This requires two steps:

  1. Obtain a complete list of the population.
  2. Randomly select individuals from that list for the sample.
Recall that the sampling procedure must reflect the unit of analysis. In a study where the unit of analysis is the student, the researcher must obtain a complete list of every student in the target population to achieve simple random sampling. This is rarely possible, so very few, if any, educational studies use simple random sampling.

Another factor to consider is the word random. Random is a technical term in social science research that means that selection was made without aim, reason, or patterns. If any study uses the word random, it means that specific scientific procedures were used to ensure that the sample was selected purely by chance. Scientists have developed a few procedures that must be followed for a study to achieve random, such as the hat-and-draw method or a random number table. To be random, participants cannot be chosen because of their intelligence, gender, social class, convenience, or any other factor besides scientifically-agreed upon random procedures. Using the word random when the unit of analysis was not selected by the hat-and-draw method or a random number table is either irresponsible or flat-out untruthful.

Why do you think there is a need to know the sampling procedure and the sample?

Stratified Random Sampling
In stratified random sampling, the researcher first divides the population into groups based on a relevant characteristic and then selects participants within those groups. In educational research, stratified random sampling is typically used when the researcher wants to ensure that specific subgroups of people are adequately represented within the sample. For example, a research study examining the effect of computerized instruction on maths achievement needs to adequately sample both male and female pupils. Stratified random sampling will be used to ensure adequate representation of both males and females. Stratified random sampling requires four steps:

  • Determine the strata that the population will be divided into. The strata are the characteristics that the population is divided into, perhaps gender, age, urban/rural, etc.
  • Determine the number of participants necessary for each stratum. Perhaps the researcher wants equal representation within the strata: half male, half female; 20 children age 5, 20 children age 6, and 20 age 7; etc. Other times (e.g., large survey research), the researcher might want to use proportionate random sampling. This requires that the researcher first knows the proportion of the group in the entire population and then match that proportion within the sample. For example, a researcher might find the most recent Nigerian census to determine that females represent 53% of the population in Nigeria, so the sample will then include 53% females.
  • Split the units of analysis into the respective strata. In other words, if the target population is students and the researcher wants to stratify based on gender, then the researcher will need two lists of the target population: one list of the male students and another list of the female students.
  • Randomly sample participants from within the group. Using either the hat-and-draw method or a random number table, randomly select the requisite number of males and do the same for the females.

Why do you think there is a need to know the sampling procedure and the sample?

Purposive Sampling
In purposive sampling, the researcher uses their expert judgment to select participants that are representative of the population. To do this, the researcher should consider factors that might influence the population: perhaps socio-economic status, intelligence, access to education, etc. Then the researcher purposefully selects a sample that adequately represents the target population on these variables.

Multi-Stage Sampling
More frequently, educational researchers use multi-stage sampling. In multi-stage sampling, the sample is selected in multiple steps, or stages. For example, in the first stage, geographical regions, such as local government areas, are selected. In the second stage, perhaps schools may be selected. In the third stage, the unit of analysis - perhaps teachers or students, are sampled. If the unit of analysis is not selected in the first step, then the sampling procedure is multi-stage sampling. In multi-stage sampling, other sampling techniques may be used at the different stages. For example, the first stage may use random sampling, the second stage may use purposive sampling, and the third stage may use stratified sampling.

The steps in multi-stage sampling are as follows:

  • Organize the sampling process into stages where the unit of analysis is systematically grouped.
  • Select a sampling technique for each stage.
  • Systematically apply the sampling technique to each stage until the unit of analysis has been selected.

Why do you think there is a need to know the sampling procedure and the sample?


Conclusion

Recall that the key question in sampling is How representative is the sample of the target population? Therefore, the researcher has the burden of demonstrating in their report (primarily in the methods section) that their sample, regardless of how it was chosen, represents the target population. Simple random sampling or multi-stage sampling will typically answer this question the best. However, as long as the researcher makes a convincing argument in their methods section that their sample adequately represents the target population, the researcher really can use any available sampling procedure.


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Copyright 2012, Katrina A. Korb, All Rights Reserved

Why is there a need for a sampling procedure?

The primary goal of sampling is to create a representative sample, one in which the smaller group (sample) accurately represents the characteristics of the larger group (population). If the sample is well selected, the sample will be generalizable to the population.

Why is it important to choose the appropriate research design and sampling procedure of your research study?

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources. This allows you to draw valid, trustworthy conclusions.

What a sample is and why is there a need to have a sample for a research?

In research terms a sample is a group of people, objects, or items that are taken from a larger population for measurement. The sample should be representative of the population to ensure that we can generalise the findings from the research sample to the population as a whole.

Why is it important to use sampling techniques in selecting a sample from the population in doing quantitative research?

It would normally be impractical to study a whole population, for example when doing a questionnaire survey. Sampling is a method that allows researchers to infer information about a population based on results from a subset of the population, without having to investigate every individual.