# 6-Sampling theory is a study of relationships existing between a population and samples drawn from the population. Sampling theory is applicable only to random samples . For this purpose the population or a universe may be defined as an aggregate of items possessing a common trait or traits.

4- Sampling is process where certain number of people are selected from the population, these selected people will represent the whole targeted population and the theory concerning sampling process is known as sampling theory (Grove, Gary, & Burns, 2015).

The sampling theory is commonly used to gather information related to population in medical, social, business, psychological sector. The sampling is done as it is not possible to do research on everyone thus, they are selected based on the topic or area of research (Ullah, 2018). For example, a research is to be conducted on “average age of marriage of women in Nepal.” Here, sampling can be done by selecting 10 families from each state, that includes 10 different states, from the whole country, this makes the data collection easier as it includes 100 families and is unbiased as number is equally distributed.

Generalizability is the effectiveness of the research, as effective and successful research is known to have good Generalizability. It is essential in Nursing research as our research are mainly related to health of people or health related problems of them.

**References:**

Grove, S. K., Gray, J., & Burns, N. (2015). *Understanding nursing research: Building an evidence-based practice*. St. Louis, MO: Elsevier.

Ullah, M. I. (2018, November 02). Sampling theory, Introduction and Reasons to Sample. Retrieved from http://itfeature.com/statistics/sampling-theory-introduction-and-reasons-to-sample

5- Sampling theory is the field of statistics that is involved with the collection, analysis and interpretation of data gathered from random samples of a population under study. In the application of the sampling theory, it is concerned with the proper selection of observations from the population that will constitute the random sample, the use of probability theory, along with prior knowledge about the population parameters, to analyze the data from the random sample and develop conclusions from the analysis. The normal distribution, along with related probability distributions, is most heavily utilized in developing the theoretical background for sampling theory (Sampling Theory, n.d.). For example, finding out the percentage of damaged tools produced during a given 5-day week in a specific factory by examining 30 tools daily at a specific time. All the tools produced in this case during the week represents the population, while the 150 selected tools during 5-days constitute a sample.

Generalization is the act of reasoning that involves drawing broad inferences from particular observations, it is widely-acknowledged as a quality standard in quantitative research but is more controversial in qualitative research (Polit & Beck 1970). It is important in nursing research as it provides the ability to generalize results allows researchers to interpret and apply findings in a broader context, making the finding relevant and meaningful.

References

Key Issues in Quantitative Research – Center for … (n.d.). Retrieved from https://cirt.gcu.edu/research/developmentresources/research_ready/quantresearch/keyissues

Polit, D. F., & Beck, C. T. (1970, January 01). Generalization in quantitative and qualitative research: Myths and strategies. – Semantic Scholar. Retrieved from https://www.semanticscholar.org/paper/Generalization-in-quantitative-and-qualitative-and-Polit-Beck/a2018b430beae56c41d4c293a051aded822a2f19

sampling Theory (n.d.). Retrieved from https://course-notes.org/statistics/sampling_theory

6-Sampling theory is a study of relationships existing between a population and samples drawn from the population. Sampling theory is applicable only to random samples . For this purpose the population or a universe may be defined as an aggregate of items possessing a common trait or traits.

Example: We may wish to draw conclusions about the percentage of defective bolts produced in a factory during a given 6-day week by examining 20 bolts each day produced at various times during the day. Note that all bolts produced in this case during the week comprise the population, while the 120 selected bolts during 6-days constitute a sample.

Generalizability refers to the extension of a research finding as well as conclusions from the study conducted on sample population to the large population.

Example: W hen a person wants to find out the percentage of people who smoke in a certain country. A sample would be taken in order to represent the entire population as well as findings taken to represent the general population.

References

Burns, N., Grove, S. (2011). Understanding Nursing Research, 5th Edition. [ Pageburstl ]. Retrieved from https://pageburstls.elsevier.com/#/books/978-1-4377-0750-2/