Samples

Simple Random Sample

when every person or item in a group has an equal chance of being chosen, and the selection is completely random — like picking names from a hat

stratified sample

is when you first divide a group into subgroups (strata) based on a shared trait (age), then randomly pick from each subgroup to get a mix from all parts of the whole group

clustered sample

when you divide a group into smaller groups (clusters), then randomly pick whole clusters to be part of your sample

systematic sampling

when you pick every nth person or item from a list, starting at a random point

voluntary sample

when people choose themselves to be part of the sample by volunteering to respond — like answering a survey online by choice

convenience sample

when you choose people who are easy to reach or nearby, not randomly — like the first five people you see

a sampling method produces the best estimates if there is

• low bias

• low variability