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In 75 to 100 words, explain briefly why you agree with post below, add a contribution and support your explanation with at least one reference.
Sampling theory refers to the research method of choosing a small sample of a population to gain
insight on the population as a whole. It is unrealistic to gather data from every single person who fits
into the research criteria, so instead this small sample known as the “sample population” provides data
that can then be utilized to understand the larger group or the “target population.” It is important to
select a sample group that accurately reflects the target population, and to do so researchers utilize
various sample methods. The two overarching types of sampling methods are probability and non
probability. Probability means that every person in the target population has an equal chance of being
chosen for the study. Non probability means that not every member of the target population has an
equal chance of being chosen (Elfil & Negida, 2017).
An example of research using a probability sample method is “A randomized clinical trial of an
intervention to relieve thirst and dry mouth in intensive care unit patients” conducted by the Intensive
Care Medicine Journal (Puntillo, Arai, & Nelson, 2014). This study used a single blind, randomized
method to pick subjects, so every patient in the intensive care unit had an equal chance of being
picked and included in the study. The study found that using a “thirst bundle” including sprays of cold
sterile water into the mouth, swabs, and mouth moisturizer to help satiate thirst in ICU patients who
are unable to have oral liquid intake decreases feelings of thirst and increases patient satisfaction
(Puntillo, Arai, & Nelson, 2014).
An example of non probability is an ad targeted at people who have had a certain issue after using a
medication. This ad will end up recruiting people who are most able to participate in the study due to
convenience and will exclude certain people who don’t have the internet and therefore won’t see the ad.
Generalizability refers to how relevant a study is to a larger population, and how accurately the dat is
able to be extrapolated on a grand scale. In order for research to be generalizable, it must be as free of
bias as reasonably possible. Selection bias can be subtle, but it is important that a sample not be
handpicked to specifically point to the hypothesis the researcher is hoping to prove. Another factor to
consider is confounding- which refers to other variables that are similar and could be causing an
impact on our study. For example, if we say that congestive heart failure and dementia are correlated
we must also think of the other common factors that increase the risk for both such as age, family
history, etc and make sure that those factors aren’t actually the ones responsible for the presumed
correlation. In this way, it becomes very difficult to fully isolate factors to study when it comes to
medical problems. The less bias and the most reliability a study boasts the more able it is to be
accurately generalized to the greater population (Kukull & Ganguli, 2012).
Generalizability is at the root of many evidence based practices, and is utilized often in nursing theory.
By understanding sample theory and what makes a study valid, we are able to know which studies we
can extrapolate to the larger population. This helps us to make changes that are both effective and
Elfil, M. & Negida, A., (2017). Sampling method in clinical research; an educational review. Emergency
Journal Tehran, 5 (1), 52. Retrieved from
Kukull, W., & Ganguli, M. (2012). Generalizability. American Academy of Neurology, 78 (23), 1886-1891.
Retrieved from
Puntillo, K., Arai, S., & Nelson, J. (2014). A randomized clinical trial of an intervention to relieve thirst
and dry mouth in intensive care unit patients. Intensive Care Medicine, 40 (9), 1295-1302. Retrieved


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