Random sampling and stratified sampling are two important ways to collect data in statistics.

1. Random Sampling:

• In random sampling, every person in the group has the same chance of being chosen.
• An easy example is drawing names out of a hat.
• Benefits: It's simple and fair. This method works well when the group is similar.

2. Stratified Sampling:

• In stratified sampling, the group is divided into smaller sections, called strata, based on certain traits, like age or gender.
• Then, samples are taken from each of these sections.
• For example, if you want to survey a community, you might ask the same number of people from different age groups.
• Benefits: This method makes sure that all groups are represented, leading to more accurate results.

When it comes to sample size, bigger samples usually give better outcomes in both methods. This means the results are more trustworthy for making conclusions.