Final answer:
Stratified sampling requires dividing a population into strata and randomly selecting a representative sample from each, ensuring that all relevant classifications are adequately represented.
Step-by-step explanation:
The process of stratified sampling involves dividing the population into separate groups known as strata. Each stratum should represent a distinct characteristic or classification pertinent to the study. For example, considering various habitat types would align with stratified sampling as it ensures proportional representation from each habitat in the sample. To perform stratified sampling correctly, one should not merely select easily accessible sites, as this can lead to a biased sample. Rather, sites should be chosen using a random method within each stratum to uphold the validity and representativeness of the sample. Ignoring ecological surveying techniques or using convenience-based site selection undermines the random aspect of stratified sampling and compromises the accuracy and validity of the conclusions drawn from the data.
In the provided scenarios:
- A soccer coach engages in stratified sampling by selecting players from different age groups.
- A pollster using a nonrandom method interviews all personnel from a select number of companies, which could be seen as cluster sampling.
- An educational researcher conducts stratified sampling by ensuring equal representation of both female and male teachers in the sample.