Sampling Designs

Question 1

Random sampling

Answer 1

• Each individual of the population has an equal chance of being selected
  
  • Ex., an instructor picks a row of students out of a hat; each row has a 1/3 chance of being selected if there are 3 rows

Question 2

Simple random sampling (SRS)?

Answer 2

• Each possible sample has an equal chance of being selected
• All SRS are random samples, but not all random samples are SRS

Question 3

Stratified sampling?

Answer 3

• Population is subdivided into 2+ groups based on pre-existing characteristics
• Another subset of units is drawn from each strata
• Not SRS (no groups of all blue, etc.)
• It is random if we take proportionately from each strata (ex., here we would take 2 red, 1 green, 1 blue)

Question 4

Cluster sampling?

Answer 4

• Population is divided into subgroups based on pre-existing characteristics
• A sample of the subgroups/clusters are censused (all individuals)
• It is random if each cluster is selected randomly

Question 5

Systematic sampling?

Answer 5

• A unit is selected as the starting point, and then additional units are sampled at a constant interval, k
  
  • k = k = total population divided by the sample size we want (ex., 100/10)
• It is random if starting point is selected randomly

Question 6

Multistage sampling?

Answer 6

• Choosing SRSs with SRSs
• Ex., an SRS of counties nationwide; then for each chosen county, an SRS of schools is chosen; lastly, within each chosen school, an SRS of classrooms is drawn