DQ 2 : Select a research article, other than the articles from your assignments, from the GCU library, Provide an overview of the study and describe the strategy that was used to select the sample from the population.

Give the overview compactly and spend the post on the sampling. The overview needs the purpose, the design, the population, the sample size, the outcome measured and the headline finding — six sentences at most. Then identify the sampling strategy precisely, using the paper's own words where you can. Probability methods include simple random, systematic, stratified and cluster sampling; non-probability methods include convenience, purposive, quota and snowball. Note that many published papers describe the strategy loosely or not at all, which is itself an appraisal finding worth reporting rather than a reason to give up. Say where in the article the strategy is described, because a single buried sentence is itself a finding.Say where in the article the description appears, because a sampling strategy buried in a single sentence of the methods is a signal about how much attention it received. Effectiveness is a fit judgement, and fit cannot be assessed until the study's own aim is on the table.

The effectiveness judgement is where the marks are and it has to be relative to the study's aim. Ask four questions. Did the accessible population match the target population the conclusions are about, and if not, who is missing? Was the size adequate — is there a power calculation, and if not, was the study large enough to detect an effect worth detecting? What selection bias does the method admit: convenience sampling in a clinic waiting room systematically excludes people who do not attend, and snowball sampling recruits within networks so it reproduces whatever those networks share. And does the paper's conclusion stay inside what the sample supports, which is the commonest failure — a convenience sample of two hundred nurses at one hospital supporting a claim about nurses generally. Support your verdict, and remember that a well-chosen non-probability sample beats a badly executed random one, so the judgement is about fit rather than about rank.