When we talk about sampling, there are two main ways to do it: random sampling and stratified sampling. Let’s break down the differences between them.

1. What They Are:

   • Random Sampling: In this method, everyone in a group has the same chance of being chosen. It's like picking names out of a hat.
   • Stratified Sampling: Here, the group is split into smaller groups based on similar traits. Then, samples are taken from each of these smaller groups. For example, if you want to study students, you might divide them by their year or gender.

2. Why We Use Them:

   • Random Sampling: This method aims to avoid bias. It helps make sure that the sample reflects the whole group.
   • Stratified Sampling: This method helps to get a good mix of different subgroups. It's helpful when some groups are small but still important.

3. An Example:

   • Imagine you want to ask students at a school about their favorite subject. A random sample might mean you just pick 10 students randomly. On the other hand, a stratified sample would mean you pick, say, 5 students from Year 11, 5 from Year 12, and so on, to make sure every year is included.

In short, use random sampling when you want an overall idea of the group. Use stratified sampling when you need to make sure specific subgroups are included!