A(n) _______ sample is obtained by dividing the population into groups and selecting all individuals from within a random sample of the groups.

Verified step by step guidance

1. Understand the problem is asking for the name of a sampling method where the population is divided into groups, and then entire groups are selected randomly.
2. Recall that in sampling methods, when the population is divided into groups called clusters, and then some clusters are chosen at random, including all members of those clusters, this method is known as cluster sampling.
3. Differentiate this from stratified sampling, where samples are taken from each group rather than entire groups being selected.
4. Recognize that the key characteristic here is selecting entire groups (clusters) randomly, not individuals within each group.
5. Conclude that the correct term to fill in the blank is 'cluster' sample.

Key Concepts

Stratified Sampling

Stratified sampling involves dividing the population into distinct subgroups or strata based on shared characteristics, then randomly sampling individuals from each stratum. This ensures representation from all groups but does not select entire groups.

Cluster Sampling

Cluster sampling divides the population into groups, called clusters, and then randomly selects entire clusters to include all individuals within them. It is useful when populations are naturally grouped and can reduce data collection costs.

Random Sampling

Random sampling is a method where every individual or group in the population has an equal chance of being selected. It helps to avoid bias and ensures that the sample represents the population fairly.