The best sampling method for the data analyst’s need is C. Stratified sampling.
Stratified sampling is a type of probability sampling that involves dividing the population into homogeneous groups or strata based on some characteristic, such as state, and then randomly selecting a proportional number of individuals from each stratum.Stratified sampling ensures that every group is adequately represented in the sample, and reduces the sampling error and variability12
Systematic sampling is not correct, because it involves selecting every nth individual from the population, starting from a random point.Systematic sampling does not guarantee that every state will have a similar proportion of data in the sample, and may introduce bias or error if there is a hidden pattern or order in the population12
Convenience sampling is not correct, because it involves selecting individuals who are easily accessible or available to the researcher.Convenience sampling is a type of non-probability sampling that does not involve random selection, and may result in a biased or unrepresentative sample12
Random sampling is not correct, because it involves selecting individuals from the population at random, without any grouping or stratification. Random sampling may not produce a sample that has a similar proportion of data from every state, especially if the population is large or heterogeneous.Random sampling may also have a higher sampling error and variability than stratified sampling12
