If a polling organization must be especially careful to represent all regions of the United States, which type of sampling plan is most useful?

Cluster Sampling

Step-by-step explanation:

Cluster sampling is the method in which the population is divided into groups - usually geographically. These groups are known as clusters or blocks. The clusters are then selected randomly, and each element in the selected clusters are used.

In this example the clusters can be the regions of the United States.

Quota sampling will be the best for a poll that represent all regions of the United States

Step-by-step explanation:

Sampling can either have a sense of probability to it or can be non-probabilistic. However, the right sampling method must be one that assures one of the most accurate answers. Two examples of sampling methods requiring probability include simple random and systematic sampling. The non-probability sampling method include quota sampling and judgment sampling

1. Simple random sampling: This entails choosing individuals based on chance; it does not have a streamlined condition for selection hence in the polling example, respondents will be selected by chance, which wont guarantee a selection from all regions of the United States.

2. Systematic sampling: in this sampling method, individuals needed for sampling are chosen at regular intervals based on predefined condition. For example, if 20 people are to be selected from a population of 500 people, systematic sampling require numbering them and selecting the 20/500 = 1/25th person which implies that the 25th, 50th, 75th, 100th, ... person will be selected. This is however not applicable to the poll as selection may not satisfy the underlying condition for the poll.

3. Judgment Sampling: This entails selective sampling using pre-defined selection requirements. It is however subjective as it depends on the researcher to determine the target population and representative samples. In the case of the poll, using a judgment sampling will be inappropriate as the researcher does not have full control over the population hence selecting respondents from all regions of the US may be impossible.

4. Quota Sampling: This method entails sampling whereby until a pre-set condition is met in the required proportion, the sampling continues. For example, in the polling organization, designing the survey to include regions; this may be though a drop down list while setting a criteria in the survey that until all regions are selected, the poll should continue. Likewise, the number of respondents from each region can be set as a quota by defining the limitations to the number of people who can respond to the poll based on regions. This may be exemplified by putting for example 10 respondents from each region as the condition such that once 10 people have filled the poll from one region, that region will no longer show on the region drop down list. This implies that poll can finally close after all the regions have been chosen in the designed quota frame.