# NRS 433 Describe sampling theory and provide examples to illustrate your definition

## NRS 433 Describe sampling theory and provide examples to illustrate your definition

NRS 433 Describe sampling theory and provide examples to illustrate your definition

Sampling theory is the study of the relationship between a given population and portion picked randomly as a representation of the whole population (McNiff & Petrik, 2018). Sampling theory can be considered biased since the researcher is picking the population group they want to study. An example of sampling is when the researcher takes a group of individuals such as smokers and start them on nicotine patches to see if helps smokers quit smoking.

Generalizability is the extension of research findings or conclusion made from sample during a research large population (Polit, 2010). As the example previously stated in the text the researcher is generalizing the smoking population that nicotine patches will help with smoking cessation when it probably won’t help everyone. The healthcare field care is sometimes based on generalization due to medications that work for most people to manage ailments, however some medical institutions are trying to push for individualize care plans for patients.

### References:

McNiff, P & Petrik, M. (2018). *Nursing research: Understanding methods for best practice.*Retrieved from https://lc.gcumedia.com/nrs433v/nursing-research-understanding-methods-for-best-practice/v1.1

Polit, D. F. (2010). Generalization in quantitative and qualitative research: Myths and strategies. Retrieved from https://www.sciencedirect.com/science/article/pii/S0020748910002063

Sampling theory is a method of research that is utilized to draw conclusions about a larger population via the utilization of samples. Since it isn’t really feasible for researchers to conduct studies on every single individual in a population, they conduct research on samples “ that accurately represent the population from which they are taken and to which inferences will be made” (American Psychological Association, 2007). An example of this would be surveying a sizable group of preschoolers of different demographics and ages about what their favorite lunch item is instead of surveying the entire school. Since the sample is meant to represent the entire population, researchers must figure out “ how best to account for subsets of cases that are not well represented (or are overrepresented) in the population” (American Psychological Association, 2007) in order for the research to be properly generalized. For example, if you take a sample of individuals from high socioeconomic status and conduct a survey based on their yearly income, you cannot generalize that survey and say that this is what everyone in that population makes since only one demographic was represented. The sampling method and its generalizability can be applied to nursing research as it allows us to research patients and nursing interventions in an efficient and relatable manner which can then be translated back to a larger population. For example, researching interventions commonly used in healthcare to prevent pressure injuries as well as interviewing a sample of patients who have had pressure injuries can help us as nurses see what were common factors that lead to these pressure injuries. This is useful as it allows us to identify factors that need to be addressed to lower the prevalence of pressure injuries without costing an institution too much money and time conducting research on an entire population rather than utilizing an appropriate sample.

### References:

American Psychological Association. (2007). *APA Dictionary of Psychology*. American Psychological Association. Retrieved from https://dictionary.apa.org/sampling-theory

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Sampling theory is a method used to find the most cost-effective way to get an answer via research. Sampling takes on a body of principles by drawing samplings that can represent the population that is being researched. (dictionary.apa.org) Sampling is important for researchers because it saves time, saves money and you can collect richer data. (Moss A, PHD) There are different types of sampling methods probability which includes simple random sampling, cluster sampling, systematic sampling, non-probability sampling which includes convenience sampling, snowball sampling, quota sampling. An example of sampling theory is if a drug manufacturer wants to know the side effects, so the researcher uses people from different demographics and does the research and receives feedback from the participants. (questionpro.com) Another example would be wanting a sample from a high school researching athletes instead of choosing every single athlete in the school you choose one or two from each sports team and gather your information for your research another example would be researching on stress and nurses in the hospital choose one from every shift every department and do your research. Generalizability is measuring how useful the results of your research study are. Generalizability is considered good if different types of participants or situations are used. (Hydroassoc.org 11/2021)

### APA Dictionary of Psychology

Moss, A. PHD What Is the Purpose of Sampling in Research? | CloudResearch

Types of Sampling: Sampling Methods with Examples | QuestionPro

11/2021 Hydrocephalus Research 101: Generalizability (hydroassoc.org)

The selection process used to study any population is called sampling. In research the sample is the data collected from population of interest and the purpose of sampling is select a population of interest from larger population on characteristics of relevance to the research question ((Sampling, n.d.) . There are 2 major types of sampling: probability sampling, and non-probability sampling. The first one is probability sampling where the sample is collected through random selection of person or community and by doing so each person has an equal chance of becoming a participant. Probability sampling will have a more accurate representation of population because of the random sampling. One example of probability sampling is a study conducted by Lucas, A., & St. James-Roberts, I. (1998) on the difference in mood and crying of breast fed vs formula fed babies , random sampling was used for this study. There area few different types of probability sampling such as *Stratified random sampling, interval sampling and cluster sampling.*

*** Non Probability sampling does not involve random sampling* and hence cannot rely on probability theory to ensure that it is representative of the population of interest (Sampling, n.d.-b). Some examples of non probability sampling are convenient sampling (where the sample is selected based on availability and accessibility ), judgmental sampling ( subjects are selected by the choice of the researcher ), and snow ball sampling . The major drawback of the non probability sampling is that there can be sampling bias affecting the research outcome. One example for the non probability sampling is research by Wright, et, al (2021),on health education intervention among older African American women living with hypertension,

Generalizability is used to assess the quality of research results in both quantitative and qualitative research .considered a major criterion for evaluating the quality of a study in quantitative research. In health care research the generalization, is an act of reasoning “that involves drawing broad inferences from particular observations, is widely-acknowledged as a quality standard in quantitative research, but is more controversial in qualitative research” (Polit & Beck, 2010). Generalization is essential in nursing practice as nursing practice rely on nursing experience. Three are three models of generalization, and they are sample-to-population (statistical) generalization, analytic generalization, and case-to-case transfer.

Sampling. (n.d.). Https://Www.Nlm.Nih.Gov. Retrieved February 18, 2022, from https://www.nlm.nih.gov/nichsr/stats_tutorial/section2/mod1_sampling.html

Polit, D. F., & Beck, C. T. (2010). Generalization in quantitative and qualitative research: Myths and strategies. International Journal of Nursing Studies, 47(11), 1451–1458. https://doi.org/10.1016/j.ijnurstu.2010.06.004

Elfil, M., & Negida, A. (2017). Sampling methods in Clinical Research; an Educational Review. Emergency (Tehran, Iran), 5(1), e52.

Wright, K. D., Jones, L. M., Adams, I. R., Moss, K. O., Harmon-Still, C., Nguyen, C. M., Rose, K. M., & Klatt, M. D. (2021). Co-created health education intervention among older African American women living with hypertension. EXPLORE. https://doi-org.lopes.idm.oclc.org/10.1016/j.explore.2021.02.004

Lucas, A., & St. James-Roberts, I. (1998). Crying, fussing, and colic behaviour in breast- and bottle-fed infants. *Early Human Development*, *53*(1), 9–18. https://doi-org.lopes.idm.oclc.org/10.1016/S0378-3782(98)00032-2

Sampling theory involves the collection of random samples and how those samples are researched based on that data analysis. Sampling theory can be provided by an area of the county people live in than further broken down to each township. For instance, Brown County consists of many small communities and the ethnicities may be studied for their prevalence in each township. A sample of each area is taken and analyzed.

Generalizability is the ability to summarize results from data analysis in an attempt to predict future study outcomes. If the information generalized is a focused group there may be a poor generalizability. A broader group such as how many people go to school in a large city may give a good generalizability.

### References:

McNiff, P. and Petrick, M. (2018). Quantitative Research: Ethics, Theory, and Research. In Grand Canyon University (Ed.) Nursing Research Understanding Methods for Best Practice (1st ed.). Ch. 3 https://lc.gcumedia.com/nrs433v/nursing-research-understanding-methods-for-best-practice/v1.1

McNiff, P & Petrik, M. (2018). Nursing research: Understanding methods for best practice.Retrieved from https://lc.gcumedia.com/nrs433v/nursing-research-understanding-methods-for-best-practice/v1.1

**Sampling theory and generalizability**

Sampling is a statistical term used to mean studying the relationship between a given population and a portion of that whole population. There are two sampling methods: probability and non-probability (Berndt, 2020). When researchers choose samples from a larger group, they use a probability-based strategy to make sure they pick the best ones. This sampling method considers every person in the population and makes samples certain. It eliminates bias and makes sure that each member has an equal chance to represent the population. Simple random sampling, cluster sampling, systematic sampling, and stratified sampling are some of the methods in this group. The non-probability method relies on the researcher or sample selection abilities instead of a predetermined process for getting input. In this type of method, the results of a survey that doesn’t use a precise sample are usually skewed and may not accurately represent the group the survey is meant to reach. It uses different sampling methods, like snowball sampling, convenience sampling, quota sampling, and judgmental sampling. In research, generalizability occurs when findings may be applied to a larger population (Kamper, 2020). One must consider carefully whether research findings may be applied to others other than the one being studied. To accomplish this, you must better understand the ailment that is prevalent in the group you are investigating, the treatment you intend to apply, and the patient. Finally, doctors must determine the generalizability of a study and the weight to place on it when making treatment decisions.

### References

Berndt, A. E. (2020). Sampling methods. *Journal of Human Lactation*, *36*(2), 224-226. https://doi.org/10.1177/0890334420906850

Kamper, S. J. (2020). Generalizability: Linking evidence to practice. *Journal of Orthopaedic & Sports Physical Therapy*, *50*(1), 45-46. https://doi.org/10.2519/jospt.2020.0701

Sampling theory can be defined as the study which involves the research based on the collection of data, analysis, as well as interpretation of the random samples that are being collected. It also includes the proper distribution which is related to the probability distributions (McNiff and Petrick, 2018). Population can be categorized in terms of geographical locations, income, age groups, and many other categories. The population can be a narrow or a broad group as per the requirement. It would appear clearer with sampling theory examples. For instance, if you are willing to conclude making statistical analysis about a topic on the adults, then the population can be a huge broad group. And on the other hand, if you are researching a particular company, then the population is a narrow one. The whole set of elements or entities is referred to as population.

Generalizability involves the findings of the research. It means the conclusion obtained by a random selection of the sample for the study. The larger the sample, the selection will be, there could be generalized results. It is a measure of how useful the results of a study are for a broader group of people or situations. Results are said to have poor generalizability if they can only be applied in a very specific situation or to a very narrow population (McNiff and Petrick, 2018).

McNiff, P., & Petrick, M. (2018). *Quantitative Research: Ethics, Theory, and Research*. Retrieved from Nursing Research: Understanding Methods for Best Practice: https://lc.gcumedia.com/nrs433v/nursing-research-understanding-methods-for-best-practice/v1.1/#/chapter/3

Upadhyay, I. (2020) Sampling Theory: Process, Types, and ST Methods. https://www.jigsawacademy.com/blogs/data-science/sampling-theory/#:~:text=Definition%20of%20Sampling%20Theory%20The%20sampling%20theory%20definition,accuracy%20in%20bringing%20out%20the%20correct%20statistical%20information.