Types of sampling

• Random Sampling

  Simple Random Sampling

  Systematic Sampling

  Stratified Sampling
• Simple Random Sampling

  Requires a sampling frame and a list of people or things. Each person or thing is allocated a unique number and then the numbers are chosen at random using either a random number generator or lottery sampling. Lottery sampling is when the numbers are chosen from a hat.
• Simple Random Sampling advantages

  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
• Simple Random Sampling disadvantages

  not suitable when the population size or the sample size is large

  a sampling frame is needed
• Systematic Sampling

  The required elements are chosen at regular intervals from an ordered list.

  sample size: 20, population: 100, you would take every 5th person (100/20=5) and the first person would be chosen randomly
• Systematic Sampling advantages

  simple and quick to use

  suitable for large samples and large populations
• Systematic Sampling disadvantages

  a sampling frame is needed

  it can introduce bias if the sampling frame is not random
• Stratified Sampling

  The population is divided into mutually exclusive strata (i.e. males and females) and a random sample is taken from each.

  (number in stratum/number in population) * overall sample size
• Stratified Sampling advantages

  sample accurately reflects the population structure

  guarantees proportional representation of groups within a population
• Stratified Sampling disadvantages

  population must be clearly classified into distinct strata

  selection within each stratum suffers from the same disadvantages as simple random sampling
• Non Random Sampling

  Quota Sampling

  Opportunity Sampling
• Quota Sampling

  An interviewer or researcher selects a sample that reflects the characteristics of the whole population.

  Population is divided into groups according to a given characteristic. The size of each group determines the proportion of the sample that should have that characteristic. An interviewer would meet people, assess their group and then, after the interview allocate them into the appropriate quota. This continues until all quotas have been filled. If a person refuses to be interview or the quota into which they fit is full then the interviewer ignores them and moves onto the next person.
• Quota Sampling advantages

  allows a small sample to still be representative of the population

  no sampling frame required

  quick, easy and inexpensive

  allows for easy comparison between different groups within a population
• Quota Sampling disadvantages

  no random sampling can introduce bias

  population must be divided into groups which can be costly or inaccurate

  increasing scope of study increases number of groups which adds time and expense

  non responses are not recorded as such
• Opportunity Sampling

  Taking the sample from people who are available at the time the study is carried out and who fit the criteria you are looking for.
• Opportunity Sampling advantages


  easy to carry out

  inexpensive
• Opportunity Sampling disadvantages

  unlikely to provide a representative sample

  highly dependant on individual researcher