Sampling Methods

Question 1

Simple Random Sampling

Answer 1

Steps

• list all members
• number each
• randomly select numbers

Pros

• equal probability of being chosen
• no bias

Cons
- can be impractical to list each member
- a chance a group in the population is
over/under presented

Question 2

Random Systematic Sampling

Answer 2

Steps
- list population 
- choose one individual at random
- choose every k th individual after, 
 returning to the start of the list at the end. 
 k is usually chosen to be close to 
 N (population size) / n (sample size)

Pros

• simple to execute and understand
• reduced bias

Cons
- may not be random if there is a hidden
periodic trait in the population

Question 3

Random Cluster Sampling

Answer 3

Steps
- choose a region at random
- choose individuals from the region at
random

Pros

• practical
• cost
• logistics
• requires fewer resources

Cons
- may not represent the population
- clusters may be formed under a biased
opinion

Question 4

Random Stratified

Answer 4

Steps 
- choose a simple random sample from 
  each population strata
- sample proportions are the same as 
  population proportion

Pros
- provides greater precision with the
same sample size
- may use smaller sample, cost efficient

Cons
- unpractical to list each individual
- proportion of population may not matter
/might change results

Question 5

Convenience

Answer 5

Steps
- ask for volunteers
- select subjects who happen to be
available

Pros
- convenient for researcher

Cons
- the sample doesn’t truly reflect
population

Question 6

Quota

Answer 6

Steps
- individuals are selected in order to fill a
quota based on characteristics (survey)

Pros
- time and money efficient

Cons

• distributions of any statistics are unknown
• chance of sampling bias