PROBABILITY SAMPLING METHODS

• Simple Random Sampling


  A method of choosing samples in which all the members of the population are given an equal chance of being selected
• Ways of obtaining samples through simple random sampling


  1. Roulette wheel

  2. Fishbowl method

  3. Use of tables of random numbers
• Systematic Random Sampling


  A method of selecting every nth element of a population, e.g., every fifth, eighth, ninth, or eleventh element until the desired sample size is reached
• Systematic Random Sampling


  • If you want to have a sample of 150, you may select a set of numbers like 1 to 15, and out of a list of 1,500 students, take every 15th name on the list until you complete the total number of respondents to constitute your sample
• Systematic Sampling Formula


  K = sampling interval

  N = population size

  n = sample size
• Systematic Sampling


  • Selecting one member for every nth of the population
• Systematic Sampling


  • The 200 students' names may be listed alphabetically then every 3rd student will be part of the sample
• Stratified Random Sampling


  A method where the population is divided into different strata (groups), and then the sampling follows
• Criteria used to divide a population into strata


  • Age
  • Gender
  • Educational qualifications
• Example of Stratified Random Sampling


  • A researcher will study the common effects of smoking on high school students. The researcher decides to select equal numbers of students from the freshman, sophomore, junior, and senior levels.
• Stratification


  Dividing the sample into subgroups before drawing random samples
• Cluster Sampling


  Clusters are representative samples of the population as a whole. After the clusters are established, a simple random sample of the clusters is drawn, and the members of the chosen clusters are sampled.
• Cluster Sampling


  • Sampling procedures are difficult and time-consuming
• Cluster Sampling


  • A researcher wants to interview 100 teachers across the country. It will be difficult and expensive on his part to have respondents in 100 different cities or provinces. Cluster sampling is helpful for the researcher who randomly selects the regions (first cluster), then selects the schools (second cluster), and then the number of teachers.