An investigator wants to study the vocational aspirations of visually challenged children spread over a wide geographical area. He should select his sample using

Stratified sampling suits studying visually challenged children scattered across a wide area, letting the researcher divide them into meaningful strata and sample each.

Strata such as region, age or degree of impairment ensure each relevant subgroup is represented.

Simple random sampling over a huge scattered frame is costly and may miss thin subgroups.

Purposive sampling picks cases by the researcher's judgement and yields no representative spread.

Convenience sampling takes the nearest available children and cannot represent a widespread group.

When such a population is dispersed geographically, cluster sampling by area is the classic alternative.