Random Sampling methods Flashcards
State three types of random sampling methods
Simple random sampling
Stratified random sampling
Systematic random sampling
What is simple random sampling
Every sample has an equal chance of being selected.
What is the method for simple random sampling
1) Allocate a number between 1 and N to each sampling unit
2) Using random number tables, computer or calculator to select x different number between 1 and N
3) Sampling units corresponding to these number become the sample
State three pros of simple random sampling
- it is suitable for small SAMPLES (not large populations)
- simple and easy to implement.
- Each number has a known equal chance of being selected.so BIAS FREE
State two cons of simple random sampling
- Not suitable when population size is large.
- sampling frame of the population needed or must assign a number to each member of pop.
- only random if ordered list is truly random
What is systematic sampling
Required elements are chosen at regular intervals in ordered list
What is the systematic sampling method
Take every kth elements where:
k = pop size (N) / samp size (n)
starting at random item between 1 and 𝑘.
State two pros of systematic sample methods
- Simple and quick to use.
- Suitable for large samples/ populations.
State two cons of systematic sample methods
- Sampling frame again needed.
- Can introduce bias if sampling frame not random
In what instance would systematic sampling not be random
systematic sampling is not random if there are patterns in the data or if the sampling frame is not random
What is the stratified sampling method
Population divided into groups (strata) and a simple random sample carried out in each group.
Same proportion (𝑠𝑎𝑚𝑝 𝑠𝑖𝑧𝑒 (𝑛))/(𝑝𝑜𝑝 𝑠𝑖𝑧𝑒 (𝑁) ) sampled from each strata.
Used when sample is large and population naturally divides into groups.
FIRST PERSON MUS BE SELECTED AT RANDOM
State two pros of stratified sampling
- Reflects population structure.
- Guarantees proportional representation of groups within the sample
State two cons of stratified sampling
- Population must be clearly classified into distinct strata.
- Selection within each stratum suffers from same disadvantages as simple random sampling