sampling

• Sample in research


  A subset of individuals from a larger population
• Population


  The complete set group of individuals, whether that group comprises a nation or a group of people with a common characteristic
• Population


  • If the ABS-CBN network has 11,000 employees having the required blood type in a certain study, then we have a population of size 11,000
• Random sampling


  A sampling method of choosing representatives from the population wherein every sample has an equal chance of being selected. Accurate data can be collected using random sampling techniques.
• Types of random sampling

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


  • The most basic random sampling wherein each element in the population has an equal probability of being selected
• Systematic random sampling


  • A random sampling that uses a list of all the elements in the population and then elements are being selected based on the kth consistent intervals. To get the kth interval, divide the population size by the sample size.
• Stratified random sampling


  • A random sampling wherein the population is divided into different strata or divisions. The number of samples will be proportionately picked in each stratum that's why all strata are represented in the samples.
• Cluster sampling


  • A random sampling wherein the population is divided into clusters or groups and then the clusters are randomly selected. All elements of the clusters randomly selected are considered the samples of the study.
• Probability sampling


  The selection of a sample from a population, when this selection is based on the principle of randomization, that is, random selection or chance.
• Non-probability sampling


  A sampling technique in which the researcher selects samples based on the subjective judgment of the researcher rather than random selection. It is a less stringent method. This sampling method depends heavily on the expertise of the researchers. It is carried out by observation, and researchers use it widely for qualitative research.
• Purposive sampling


  A non-probability sampling technique where the researcher selects the samples based on the goal of the studies of the researcher. This excludes other samples from being selected.
• Situation 1


  A researcher writes the name of each student on a piece of paper, mixes the papers in a bowl, and draws 7 pieces of paper
• Situation 1


  Illustrates simple random sampling. The pieces of paper correspond to each student as an element of the population. All of them have an equal chance of being selected as a sample by randomly picking 7 pieces of paper in a bowl.
• Situation 2 and 3

  1. A researcher selects every 7th student from a random list

  2. A researcher tells the class to count and then selects those students who count a multiple of 7 numbers
• Situation 2 and 3

  Illustrate systematic random sampling because samples are being selected based on the kth consistent intervals. Selecting every 7th student on the random list of names creates an equal chance for all of the students to become samples.
• Situation 4


  A researcher separates the list of boys and girls, then draws 7 names by gender
• Situation 4


  Illustrates stratified random sampling because the students are divided into two different strata or groups, boys and girls. With a proportional number for each group, samples are then selected at random from these two groups.
• Situation 5


  A researcher surveys all students from 3 randomly selected classes out of 7 classes
• Situation 5


  Illustrates cluster sampling since all students are divided into clusters or classes, then 3 classes are selected at random out of the 7 classes. All of the students of these three classes comprised the samples of the study. Take note that each cluster is mutually homogeneous yet internally heterogeneous.
• Stratified Sampling


  • The teacher randomly selects 20 boys and 15 girls from a batch of learners to be members of a group that will go to a field trip
• Simple Random Sampling


  • A sample of 10 mice are selected at random from a set of 40 mice to test the effect of a certain medicine
• Cluster Sampling


  • The people in a certain seminar are all members of two of five groups are asked what they think about the President
• Convenience Sampling


  • A brand manager of a toothpaste asks ten dentists that have clinic closest to his office whether they use a particular brand of toothpaste
• Systematic Sampling


  • A barangay health worker asks every four house in the village for the ages of the children living in those households
• Parameters


  A measure that describes a POPULATION. Examples: Population Mean, Population Variance, Population Standard Deviation
• Statistics


  A measure that describes a SAMPLE. Examples: Mean, Variance, Standard Deviation