When determining the impact of a variable, which is NOT a necessary consideration?

In research, particularly when assessing the impact of a variable, various factors must be considered to ensure the results are valid and meaningful. Random sampling, while beneficial for ensuring the generalizability of findings to a broader population, is not strictly necessary for determining the impact of a variable within a specific sample. It is possible to analyze data from a non-random sample and still draw conclusions about the relationships and effects present in that data; however, those conclusions may not extend to the wider population if the sample is biased.

Effect size is crucial because it quantifies the magnitude of the impact and helps researchers understand the practical significance of their findings. Sample size is also vital, as larger samples generally provide more reliable estimates of the population parameters and reduce the likelihood of statistical errors. The reliability of statistical tests ensures that the findings are consistent and replicable across different studies or samples.

Thus, while all of these considerations add value to research, random sampling is not a determining factor for assessing the impact of a variable within the confines of the gathered data.