Respond to the following answered question in apa style with another reference:

Question: When is sampling done and what is its purpose? How does the researcher determine sample size? How can the sample size adversely affect research? Give an example of how sample size is affected by "power analysis."

Sampling is done whenever research is being conducted via specifying how many participants will be included and how they will be selected; furthermore, this sample should represent the population or group of interest as best it can (Polit & Beck, 2022). A sample should be representative meaning that its characteristics closely match those of the population of interest and should avoid sampling bias which is over-representation or under-representation of a population portion on a characteristic relevant to the research question (Polit & Beck, 2022). A sample size too small is at risk for not being representative enough of the population and the results may not be sufficient to detect a difference between groups. Usually a bigger sample size is better especially in quantitative studies because the probability of the sample size being representative of the population increases. However, qualitative sampling usually rely on small non-probability sampling being that it will provide information rich data, with new meaning and multiple realities whereas quantitative data wishes findings that may be generalized (Polit & Beck, 2022). Power analysis allows researchers to estimate how large their samples should be for a testing hypotheses; this may be achieved by estimating how large the group difference will be on the key outcome such as a patient lowering their A1C and this is usually achieved via prior research. Furthermore, a large sample may not be so accurate if it holds sampling bias. For example you are studying how effective high school education may be in maintaining ones health but your large sample all came from a private high school. The education the private high school students acquired opposed to the public low income high school students received may be vastly different, thus the sample is biased and not representative of the population.