Hello i need a good and positive comment related with this argument .A paragraph with no more 90 words.‘
Re:Topic 2 DQ 1
In an experiment or research where it is imposable or expensive to sample the entire population, a small sample is used to conduct the research. A sampling method is the process of selecting a small group that are representative of a larger population being studied. Samples can be made in different ways. All these ways are not equally good. Most studies a random sample is used for this reason. A random sample selected in such a way that every member of the population has an equal chance of being selected (Fraenkel & Wallen). A random sampling method is designed to select a representative sample by using chance selection so that biases will not systematically alter the sample (Fraenkel & Wallen). A true random sample, that is a small set of data can give insights which can be applied to a much larger group. Simple random sampling is achieved by random selection of members from the sampling frame(Grove & Cipher, 2017).
Example; When Joint commission come for inspection to the unit, they pick one RN to interview randomly. Every nurse who work on that floor has the same chance being selected for the interview.
A sample group is used to conduct research or study there is always a chance for error because it can never fully match the entire population. It can be prevented by;
Researchers should strive to ensure that the sample population truly represents the total population. Statistical tests have built in checks to ensure true sample and the numbers can only be an estimate
Expert Solution Preview
Sampling methods are crucial in conducting research when it is impractical or costly to study the entire population. Random sampling is often preferred to ensure that every member of the population has an equal chance of being selected. This method helps to reduce biases and obtain a representative sample. A true random sample can provide valuable insights that can be applied to a larger group. However, it is important to acknowledge that a sample group may not fully match the entire population, leading to potential errors. Researchers can mitigate this by striving to ensure that the sample population truly represents the total population and by using statistical tests to estimate the precision of the findings.