sampling

• Sampling


  The process by which a researcher identifies the representative of a population to be used in his/her study
• Probability/Statistical Sampling


  • Used when an accurate representation of the entire population is needed in the sample
  • Gives all representatives of the entire population to be selected as a sample
• Probability/Statistical Sampling


  • Often used in quantitative research rather than qualitative research
  • Relies on a statistical analysis of the population
• Simple Random Sampling


  Samples are identified randomly with the help of statistical and mathematical computations
• Stratified Random Sampling


  1. The population is divided into different groups/strata based on criteria set by the researcher

  2. The researcher then randomly identifies individuals from these groups
• Cluster Sampling


  Similar to stratified randomly sampling, but instead of grouping them based on criteria set by the researchers the individuals are randomly selected from naturally occurring groups (e.g. sections in a school)
• Multistage Sampling


  1. Combination of Stratified random and cluster sampling

  2. Consists of multiple stages of grouping: first from naturally occurring groups and then groups based on criteria set by the researcher
• Systematic Sampling


  1. Researcher sets a fixed interval to determine the sample

  2. For example, in a population of 100 individuals, the researcher can choose select every 5th member until he reaches representatives
• Non probability Sampling


  • Used when the population can not/does not be sampled to represent the target population and so individuals do not have an equal chance of being sampled
  • The researcher selective of its population and sample (e.g., not individuals can be sampled, or the researcher do not need to sample all individuals)
  • Often used in qualitative research rather than quantitative research
• Purposive Sampling


  1. Samples are targeted and selected based on criterion set by the researcher

  2. Criteria are based on the research objectives and questions that the study aims to answer
• Convenience Sampling


  1. The sampling group is identified by the convenience of the researcher (e.g. nearby, already familiar)

  2. Groups are determined based on their availability rather than randomness from the population

  3. Does not guarantee an accurate representation of the population but can be useful in collecting preliminary data
• Snowball Sampling


  1. The identification of the sample group is accumulative and can come from populations not initially known by the researcher

  2. For example, if a researcher wants to study the impact of Alzheimer's on family members, but they don't know a lot of patients. They can ask the patients they know for others like them
• Quota Sampling


  1. Very similar to purposive sampling wherein the population is filtered based on a criterion set by a researcher

  2. However, in quota sampling, they are looking for specific characteristics in individuals that may or may not directly link to the research question/objective (e.g. age, sex, religion)