5.1: Introduction to Sampling

• Population


  The entire set of individuals of interest to a researcher. This sample of a population will be generalised to the entire population; also known as the target population.
• Sample


  A set of individuals selected from a population, intended to represent the population.
• What are two different types of populations?

  1. Target Population: A group defined by a researcher's specific interests.
  2. Accessible Population: The easiler available segment of a target population.
• Representativeness


  The extent to which the characteristics of the sample accurately reflect the characteristics of the general population.
• Representative Sample


  A sample with the same characteristics as the populations.
• Biased Sample


  A sample with characteristics different from those of the population.
• Selection Bias


  When participants or subjects are selected in a manner that increases the probability of obtaining a biased sample. A threat to external validity that occurs when the selection process produces a sample with characteristics from those in the population.
• Law of Large Numbers

  In the field of statistics, the principle that states that the larger the sample size, the more likely it is that values obtained from the sample are similar to the actual values for the population.
• Sampling


  The process of selecting individuals to participate in a research study.
• Sampling Methods


  The variety of ways of selecting individuals to particiapte in a research study; also known as sampling techniques or procedures.
• Probability Sampling


  A sampling method in which the entire population is known, each individuals in the population has a specifiable probability of selection, and sampling is dome using a random process based on the probabilities.
• What are the three conditions for probability sampling to occur?

  1. The exact size of the population must be known and it must be possible to list all of the individuals.
  2. Everyone in the population must have a specified probability of selection.
  3. When a group of individual are all assigned the same probability, the selection process must be unbiased so that all group members have an equal chance of people selected–a random process.
• Nonprobability Sampling


  A method of sampling in which the population is not completely known, individual probabilities cannot be known, and the selection is based on factors such as common sense or ease with an effort to maintain representativeness and avoid bias.
• Simple Random Sampling

  A probability sampling technique in which each individual in the population has an equal and independent chance of selection. This has three steps:

  1. Clearly define the population you want to select a sample from.
  2. List all members of the population.
  3. Use a random process to select individuals from the list.
• What are two principles of random sampling?

  1. Sampling With Replacement: Requires an individual selected for the sample be recorded as a sample member and then returned to the population before the next selection is made. This ensures the probability of selection remains constant throughout a series of selections.
  2. Sampling Without Replacement: Removes each selected individual from the population before the next selection is made. This guarantees that no individual appears more than once in a single sample.