**Question:** People are separated into groups, from each group people are selected randomly. What type of sampling is this?

A. Simple Random Sampling
B. Stratified Random Sampling
C. Cluster Sampling
D. Systematic Sampling

**Core Concept:** Sampling is a statistical method used to select a representative sample from a larger population to make inferences about the entire population. There are various types of sampling methods based on how the samples are selected.

**Why the Correct Answer is Right:**

B. Stratified Random Sampling

In stratified random sampling, the population is divided into subgroups (strata) based on specific characteristics, and then samples are randomly selected from each stratum. This method ensures that the resulting sample is representative of the different subgroups within the population.

**Why Each Wrong Option is Incorrect:**

A. Simple Random Sampling
Simple random sampling involves selecting individuals or objects without any pattern or consideration of characteristics. It provides an unbiased sample but may not represent specific population subgroups.

C. Cluster Sampling
Cluster sampling involves selecting clusters (groups of individuals) and then randomly selecting individuals within those clusters. This method focuses on clusters rather than individual characteristics.

D. Systematic Sampling
Systematic sampling selects every nth individual or object from a population, without considering their characteristics. It is useful when the population is large and known, but may not represent subgroups within the population.

**Clinical Pearl:**

Understanding the appropriate sampling method is crucial for accurate and representative research findings. When stratified random sampling is necessary, it ensures that the sample covers different subgroups within the population, leading to more accurate results. This is especially important in clinical studies involving diverse populations or when studying specific characteristics within a population.