Question

Describe the process of stratified sampling in terms of - Minimizing bias:

a) Randomly selecting samples without criteria
b) Ignoring habitat variations
c) Ensuring representation of all strata
d) Focusing only on a specific stratum

Answer 1

Stratified sampling involves dividing the population into subgroups (strata) and using random sampling within those strata to ensure all subgroups are adequately represented, thus minimizing sampling bias.

Step-by-step explanation:

The process of stratified sampling is a method used to minimize bias when selecting a sample from a larger population. Unlike simply picking samples randomly without criteria, stratified sampling requires dividing the population into different subgroups, known as strata, based on shared characteristics.

The key steps in conducting stratified sampling include:

1. Identify the various strata within the population that are important for the research study.
2. Use simple random sampling within each stratum to select a proportionate number of participants, ensuring that every subgroup is adequately represented and habitat variations are not ignored.

Stratified sampling does not focus only on a specific stratum; instead, it aims to include all strata to reflect the population's diversity. This process helps avoid the kind of sampling bias that can occur with nonrandom sampling methods, like convenience sampling, where certain segments of the population might have a lower likelihood of being chosen.