Which of the following sampling techniques is most suitable for selection of representative villages of an area with diversified geographical features?

The correct answer is 'Stratified-random'

Key Points

• Stratified-random:
  • Stratified-random sampling divides the population into distinct subgroups or strata that share similar characteristics, such as geographical features, before randomly sampling from each stratum.
  • This technique ensures that each subgroup is adequately represented, providing a more accurate and comprehensive representation of the area.
  • For areas with diversified geographical features, stratified-random sampling allows for the inclusion of all relevant types of terrain, climate, and ecological zones within the sample.
  • This method enhances the reliability and validity of the sample by ensuring that the diversity within the population is accurately reflected in the selected villages.

Additional Information

• Systematic:
  • Systematic sampling involves selecting elements from an ordered sampling frame at regular intervals, which might lead to unintentional bias if there is a hidden pattern in the population’s order.
  • While this method is straightforward and cost-effective, it may not effectively capture the diversity in an area with varied geographical features.
• Random:
  • Random sampling gives all individuals an equal chance of being selected, ensuring unbiased representation. However, there is a risk that some geographical features might be underrepresented or missed altogether, especially in a diverse area.
  • Without intentional stratification, the sample may not truly reflect all the varied geographical characteristics of the area.
• Clustered:
  • Clustered sampling divides the population into clusters, often based on geographical or administrative boundaries, and then a random sample of these clusters is selected.
  • While this method is useful for efficiency and reducing costs, it might not adequately represent the diversity within clusters, particularly if some clusters are more homogeneous than others.
  • For an area with diversified geographical features, the risk of selecting clusters that do not represent the whole area's variability is higher.

Important Points

• Stratified-random sampling is particularly effective when different subgroups within a population vary significantly and need to be represented proportionally.
• This sampling technique improves the precision of overall sample estimates by reducing sampling error.
• Geographical diversity can include variations in topography, climate, land use, and socio-economic factors, all crucial for comprehensive analysis and planning.
• Utilizing stratified-random sampling can lead to more equitable resource allocation and more effective policy development tailored to the specific needs of different geographic areas.