When a research problem is related to heterogeneous population, the most suitable sampling method is:

Correct option is B

When dealing with a heterogeneous population, Stratified Sampling is the most appropriate method. In this approach, the population is divided into distinct subgroups or strata based on shared characteristics (such as age, gender, income level, etc.). Researchers then draw samples from each subgroup proportionally. This ensures that each subgroup is adequately represented in the sample, which is essential for obtaining accurate and reliable results in a population with diverse characteristics.
The other options are less suitable for a heterogeneous population:
· Cluster Sampling (Option a): Primarily used when the population is geographically dispersed and divided into clusters. While efficient in certain cases, it doesn’t ensure representation of all subgroups within a heterogeneous population.
· Convenient Sampling (Option c): A non-probability sampling method, where samples are selected based on availability and convenience. This method lacks representativeness and may lead to bias.
· Lottery Method (Option d): A random sampling technique but does not guarantee proportional representation of all subgroups in a heterogeneous population.
Information Booster: 1. Stratified Sampling: Divides the population into homogeneous subgroups to ensure diversity and accuracy in results.
2. Increased Accuracy: Reduces sampling error and improves reliability by capturing each subgroup proportionally.
3. Applications: Useful in studies with diverse populations in terms of demographics, social factors, or other relevant characteristics.
4. Representative Sample: Ensures that smaller, distinct groups within a population are not overlooked.
5. Types of Stratified Sampling: Can be proportionate (sample size based on subgroup size) or disproportionate.
6. Enhanced Comparability: Allows researchers to analyze differences between subgroups within the population.