Sampling Methods Flashcards
Descibe simple random sampling
Every member of population is equally likely to be chosen. For example, allocate each member of population a number. Then use random generator to get a sample of the desired size.
State 2 pros of the simple random sampling
- Bias free
- Easy and cheap to implement
State 2 cons of the simple random sampling
- Not suitable when population size is large
- Sampling frame is needed
Describe systematic sampling
pick random number between 1-10, and take n’th number
State 2 pros of systematic sampling
- Simple and quick to use
- Suitable for large populations
State 2 cons of systematic sampling
- Sampling frame needed
- Can introduce bias if sampling frame not random
Describe stratified sampling
when population naturally divides into groups, split the population into these groups and then sample same proportion(sample/population) in each group
State 2 pros of stratified sampling
- Reflects population structure
- Guarantees proportional representation of groups within population
State 1 cons of stratified sampling
-Population must be classified in distinct strata
Describes opportunity sampling
Take samples from members of the population you have access to until you have a sample of the desired size
State 2 pros of opportunity sampling
- Easy to carry out
- Inexpensive
State 2 cons of opportunity sampling
- Unlikely to provide a representative sample
- Dependant on individual research
Describe quota sampling
Population is divided into groups depending on characteristic. Decide how many members of each group you wish to sample and use opportunity sampling until you have a large enough sample for each group
State 1 pros of quota sampling
-Allows for early comparison between different groups in groups
State 2 cons of quota sampling
- Can take time
- Non responses are not recorded