The Fast Publications is your trusted accomplice in the conversion of raw data into a taken-to-believe science. We realize that the correctness of your findings depends wholly on the honesty of your research methods with the beginning being your sample method. Our professional researchers will make sure that the research design is perfect and the manuscript is well written. We also do Scientific and Technical Editing, which ensures that your writing is of the highest standard of rigor and clarity necessary to be published in high-impact journals.
The reason to settle on Fast Publications
- Methodological Review: We confirm your sampling plan in order to maximize external validity and minimize bias.
- Accuracy in Reporting: We also masterfully hone your paper, and all the steps, such as population definition, data analysis, etc., are reported with accuracy.
- Skilled Scientific and Technical Editing: Our scientific and technical editors explain complicated ideas and match your words with the technical standards which the journal demands.
- Publication Success: We aid in the statement of your purpose to indicate why your subset of population produces valid, generalizable findings.
Willing to develop a strong framework of your research? Become a partner with Fast Publications!
Sampling Techniques Decoded: The Right Population Subset to a Valid Result
The first step in any good research paper is a critical question, Who or what are you studying? The solution is what will define your target population. Yet, it is hardly ever possible to study a whole population, that is, all consumers in a country, all cells in a tissue culture, or all stars in a galaxy. You are forced to choose a manageable sample: the sample. The procedure you adopt in selecting this subset that is your sampling technique is the foundation of the external validity of your study. The use of a poorly selected sample is bound to produce biassed, non-generalizable and ultimately invalid results. Your explanation will be refined later by Scientific and Technical Editing but good methodology must precede that.
The Two Pillars of Sampling: Non-Probability vs. Probability
There are two basic categories of sampling methods, each having its own benefits as well as applications:
Probability Sampling
In probability sampling, random selection is applied, every unit in the population is given a known and non-zero probability of being sampled. This technique discourages selection bias and enables you to transfer your results to the population within the statistical theory. It is the standard of gold when it comes to high quantitative research in regards to external validity. Simple random sampling (SRS)
All members stand equal chances of being selected. You could pick participants by a random number generator to get the members of a full list of the population. SRS has the greatest level of generalizability.
- Systematic Sampling: You choose the nth unit of the population list at random but with an initial point. This is normally more effective and time saving compared to SRS.
- Stratified Sampling: This is where you subdivide the population into discontinuous subgroups (strata) by major characteristics (e.g., age groups, income levels). A random sample of each stratum is then taken. This would make sure that your sample is a perfect reflection of the diversity of the population in those vital characteristics.
- Cluster Sampling: The population is subdivided into clusters (typically geographical units or institutions). You randomly choose a few clusters and proceed to study all the units in the selected clusters. This works well with large populations that are geographically spread, but a little more sampling error is introduced.
Non-Probability Sampling
Non-probability sampling entails non-random sampling (not based on the researcher), but depends on his or her subjective judgment or convenience. It is also more simple and cost-effective but has a greater chance of selection bias and restricts your potential to come up with strong statistical generalizations. These are normally the type of techniques that you employ in an exploratory study or a qualitative study where what you intend to accomplish is the detailed understanding as opposed to generalized results.
- Convenience Sampling: You pick individuals that are conveniently available. One such typical case is the employment of undergraduate students who can be found on campus. This is the slowest yet fastest method.
- Purposive (Judgmental) Sampling: The researcher selects participants based on their expertise of what they think are the best representatives or people most knowledgeable about the topic. This is great in case of a narrow, inaccessible population or when one is testing a theory with experts.
- Quota Sampling: It is like stratified sampling in that you determine sub groups in the population. But you fill in the quotas of each subgroup by non-random and, frequently, convenience-based means up to the necessary number.
- Snowball Sampling: The participants refer to other participants. This is necessary in case of studying rare or obscure groups (e.g., certain groups of patients, underearth communities).
The importance of Sample size is critical
The battle is half to decide which method one should choose. You will also have to find the right size. A real effect can not be observed by an underpowered study (too small a sample), and causes misleading non-significant findings. A large scale study is a wasted resource and time. To determine the required minimum sample size, you use power analysis which takes into consideration:
- The required level of statistical significance (/alpha/ usually 0.05).
- The required statistical power (1-Beta, typically 0.80).
- The lowest possible effect that you deem of importance.
Bigotry: The Unsaid Murderer of Fidelity
Whatever the approach, you have to reduce bias. Key types of bias include:
- Selection Bias: This is a process of choosing the sample in a systematic way that excludes or includes some type of units hence, a non representative sample.
- Non-Response Bias: The selected units are non-respondent (e.g., refusing a survey), and non-responders are different in a systematic manner compared to responders.
- Response Bias: The respondents distort information or provide answers which they believe that the researcher wants to hear.
You have to choose the most rigorous sampling method that fits the research question and execute it with strict care.
Fast Publications Assures Methodological Excellence
Your description of sampling is critical to success in publication. We are not merely going to fix grammar in our Scientific and Technical Editing services; we are going to make your methodology section solid, clear and justifiable. We’ll make sure that you clearly define your population, explain the technique you have chosen (whether it is stratified random or purposive sampling), and explain the reason behind the sample size.
Minimize methodological weaknesses to undermine the effect of your study. Fast Publications will give you the strength to provide a methodology that the reviewers and readers can believe in to ensure that your valuable findings have the highest level of validity.
Do you want Fast Publications to examine your suggested sampling plan and compute your needed sample size?
