W7 - Sampling Methods

• Population 


  A collection of individuals who share one or more noteworthy traits that are interest to the researcher
• Sample


  A small portion of the population selected for observation and analysis
• Sampling


  The procedure of getting a small portion of the population for research
• Designing the sample:

  • Who will be surveyed?
  • How many people will be surveyed?
  • How should the sample be chosen?
• Slovin's formula

  n= sample size

  N= population

  e= margin of error

  
• Probability sampling


  Every member of the population has a probability of being selected or included in the sample
• Types of probability sampling

  • Simple random
  • Cluster
  • Stratified random
  • Systematic
• Simple random sampling


  • Using a pure chance selection, you assure every member the same opportunity to be in the sample
  • This technique is implemented where the target population is considerably large
  • Fishball technique, roulette wheel,
• Stratified random sampling


  A large population is divided into groups (strata), members of a sample are chosen randomly from these strata
• Cluster sampling


  • Usually applied in large scale studies, geographical spread out of the population is a challenge, and gathering information will be very time-consuming
  • The main segment is divided into clusters, usually using geographic and demographic segmentation parameters.
• Systematic sampling


  • The procedure is a simple as selecting samples every nth of the chosen population until arriving at a desired total number of sample size.
  • The selection is based on a predetermined interval
• Steps in finding the sample

  1. Define the population size and sample size
  2. Calculate the sampling interval (k) by N/n
  3. Choose a random starting point
  4. Select every kth unit