# Sampling Strategies

## Sampling Strategies

Sampling Strategies 150 150 Peter

### Sampling Strategies

For this Discussion, you will first consider sampling strategies. Then, you will turn your attention to data collection methods, including their strengths, limitations, and ethical implications. Last, you will consider measurement reliability and validity in the context of your discipline.
With these thoughts in mind, if your last name starts with A through L, use Position A. If your last name starts with M through Z, use Position B.
Position A: Probability sampling represents the best strategy for selecting research participants.

Question: Post a restatement of your assigned position on sampling strategies. Explain why this position is the best strategy for selecting research participants. Support your explanation with an example and support from the scholarly literature. Next, select a data collection method (e.g., surveys, interviews, observations) and briefly explain at least one strength and at least one limitation. Then, identify a potential ethical issue with this method and describe a strategy to address it. Last, explain the relationship between measurement reliability and measurement validity using an example from your discipline.

### Sample Paper

Sampling Strategies

Sampling strategies entail the selection process, and techniques researchers apply in selecting a specific segment or portion to represent a whole population in a study. The sampling strategies are essential in research as they act as informants to detect a researcher’s work, especially on the inferences made based on the underlying findings (Onwuegbuzie & Collins, 2007). Different sampling strategies are used in scientific studies. In this case, I will focus on probability sampling.

Probability Sampling

Probability sampling represents the best strategy for selecting research participants because it allows a researcher to choose a large number of people in the population or even specific subgroups in a quantitative study (Teddlie & Yu, 2007). The participants have higher chances of being selected randomly. Therefore, the sampling technique enhances the probability of inclusion of every participant member determinable in a population. For example, in random probability sampling, a researcher can use pieces of paper with letters written on each of them. Distribute them in a specific population of the study, and sample all those with similar characters together, thus showing that participants have an equal chance of being selected (Teddlie & Yu, 2007).

Data Collection Method

Observations are fundamental data collection methods that are mostly applicable in a large study population (Mazhar et al., 2021). It is most common in studies that involve behavioral sciences. The observation method must have a formulated purpose for research in that the research must be systematically planned and recorded validly and reliably. This type of data collection method is more appropriate when studying subjects who do not require verbal responses due to personal reasons.

Strength and Limitation

The observation method is among the most used data collection methods by researchers. It has some advantages and disadvantages as well. The basic strength of this method is that it is easy to conduct, as the researcher only needs to sit back and observe the respondents without asking those questions in person (Mazhar et al., 2021). The drawback is that the data collected can be inconsistent, thus giving unreliable information. For example, a respondent’s mood can change on some days depending on how they are feeling, thus giving different responses.

Ethical Issue and Strategy to Address

The observation method should be conducted in guidance with research ethics. A potential ethical issue with this method is the lack of informed consent. Collecting personal information without the respondents’ consent bridges their rights and subjects them to danger at some point. Therefore, observational investigators must ensure that they get permission from respondents before collecting any personal information from them, such as taking videos, pictures, and recordings of their daily activities. They should communicate their main aim of collecting data, assure the respondents of confidentiality and build trust to allow them to participate willingly.

Relationship between Measurement Reliability and Validity in Nursing

The concepts of measurements of reliability and validity are essential in social research. The two concepts might sound similar, but they differ from each other in reality. Measurement of reliability interprets the concept of consistency in measurements taken at different times, different conditions with different people, and using different types of tools that work similarly (Drost, 2011). It elaborates that the results of the measurements should always be the same. The validity focuses on the meaningfulness of the research measurements. For instance, if one weighs themselves with different weighing machines and gives different results with small reasonable margins, the measurements are likely to be acknowledged as valid. The relationship between the two is that they verify the quality of a method, technique, or test of a measurement (Drost, 2011). For example, the concepts of reliability and validity measurements can help determine the change in the patient’s temperature using different medically proven measurement tools to develop their assessments.

References

Drost, E. A. (2011). Validity and reliability in social science research. Education Research and Perspectives, 38(1), 105â€“124. https://www.researchgate.net/publication/261473819_Validity_and_Reliability_in_Social_Science_Research

Mazhar, S. A., Anjum, R., Anwar, A. I., & Khan, A. A. (2021). Methods of data collection: A fundamental tool of research. Journal of Integrated Community Health (ISSN 2319-9113)10(1), 6-10. http://medicaljournalshouse.com/index.php/ADR-CommunityHealth/article/view/631/496

Onwuegbuzie, A. J., & Collins, K. M. (2007). A typology of mixed methods sampling designs in social science research. Qualitative Report12(2), 281-316. https://files.eric.ed.gov/fulltext/EJ800183.pdf

Teddlie, C., & Yu, F. (2007). Mixed methods sampling: A typology with examples. Journal of mixed methods research1(1), 77-100 https://www.dedoose.com/publications/mixed%20methods%20sampling%20-%20a%20typology%20with%20examples.pdf