1.2 Sampling

• A simple random sample of size n is one where every sample of size n has an equal chance of being selected.
• In systematic sampling, the required elements are chosen at regular intervals from an ordered list.
• In stratified sampling, the population is divided into mutually exclusive strata (e.g. males and females) and a random sample is taken from each.
• Advantages of simple random sampling

  • Free of bias
  • Easy and cheap to implement for small populations and small samples
  • Each sampling unit has a known and equal chance of selection
• Disadvantages of simple random sampling

  • Not suitable when the population size or the sample size is large as it is potentially time consuming, disruptive and expensive
  • A sampling frame is needed
• Advantages of systematic sampling

  • Simple and quick to use
  • Suitable for large samples and large populations
• Disadvantages of systematic sampling

  • A sampling frame is needed
  • It can introduce bias if the sampling frame is not random
• Advantages of stratified sampling

  • Sample accurately reflects the population structure
  • Guarantees proportional representation of groups within a population
• Disadvantages of stratified sampling

  • Population must be clearly classified into distinct strata
  • Selection within each stratum suffers from the same disadvantages as simple random sampling