Question

How can they stratify the sample in order to choose a random sample of communities within different regions and urban, suburban, and rural areas?

1) Stratify by region of the country and then choose a random sample of communities within those strata
2) Stratify by urban, suburban, and rural areas and then choose a random sample of communities within those strata
3) Divide the communities into city blocks or fixed areas as clusters and sample some of those
4) Sample everyone on the block or within the fixed area

Answer 1

To stratify the sample, one method is to create strata by region and then randomly select communities within them. Alternatively, strata can be formed by urban, suburban, and rural areas with communities then randomly selected within these strata.

Step-by-step explanation:

To stratify the sample for choosing a random sample of communities within different regions and in urban, suburban, and rural areas, you could take multiple approaches. One approach is to first stratify by the region of the country, creating strata for each region, and then from within those strata, perform a simple random sampling to select communities. This ensures that communities are adequately represented across the different regions.

Another approach could be to stratify by area type, which involves creating strata for urban, suburban, and rural areas. Following this, you would choose a random sample of communities within these specific strata to ensure all area types are represented in the sample. This method considers the population distribution across the different area types rather than the geographic regions.

Both of these methods would provide a stratified random sample which represents the overall population more accurately when compared to other sampling methods like cluster sampling or systematic sampling, which have different approaches and purposes.