Sampling Techniques

• Statistics is the art and science of gathering, analyzing, and making inferences (predictions) from numerical information obtained in an experiment.
• The numerical information is referred to as data.
• Descriptive Statistics is concerned with the collection, organization and analysis of data.
• Inferential Statistics is concerned with making generalizations or predictions form the data collected.
• Read paragraph on page 774.
• The universal set in this case is called the population.
• A subset of the population is called a sample.
• We frequently conduct a sample to predict the population.
  • It is sometimes impossible
  • It is sometimes, possible but impractical
  • It is sometimes too expensive.
• Sampling Techniques
  • Random Sampling
    • Draw a sample in such a way that every item is equally likely to be selected.
    • Use a random number generator.
  • Systematic Sampling
    • Pick every n^th item.
    • Might match, or miss, a periodic defect in the system.
  • Cluster Sampling
    • Divide the population into groups, usually based upon geography.
    • Select some of the groups at random.
    • Sample everyone in the group, or use some sampling method within the group.
    • Select city blocks, or several boxes of an item.
  • Stratified Sampling
    • Divide the population into classes by characteristics
    • Sample each class.
  • Convenience Sampling
    • Just ask/check what is easy