- Random Sampling: Where every possible participent has an equal chance of being chosen
-Advantages: Cheap, quick & easy, everyone has an equal chance of being chosen,minimise the possibility of bias
-Disadvantages: May not be representative,If the population is very heterogeneous the results can vary considerably. May be difficult to do for large/ dispersed populations.
1. Stratified Random sampling: This involves dividing the target population into non-overlapping categories called strata. A sample is then drawn randomly from each sub population.
-Advantages:If the population is heterogeneous- gives a more realistic picture than simple random, and ensures representation of key strata.
-Disadvantages: More time consuming
2. Systematic Random sampling: Names are selected from the sampling frame at regular intervals until the size of sample is reached.
-Advantages:Less chance of mistakes Particularly useful with large populations.
-Disadvantages: Results may be biased, not everyone has a chance of being chosen
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