Statistical sampling

Statistical sampling is a technique for selecting a subset (or sample) from a larger population to estimate its characteristics. This method is widely used in various fields, such as research, quality assurance, and survey methodology, because it is often impractical or impossible to collect data from every individual in the population.

Here are some key points about statistical sampling:

  1. Purpose: The main goal is to gather information about a population without surveying every member, saving time and resources.
  2. Types of Sampling Methods:
    • Simple Random Sampling: Every member of the population has an equal chance of being selected.
    • Stratified Random Sampling: The population is divided into subgroups (strata) and random samples are taken from each stratum.
    • Cluster Sampling: The population is divided into clusters, some of which are randomly selected, and all members of chosen clusters are surveyed.
    • Systematic Sampling: Every nth member of the population is selected after a random starting point.
  3. Applications: Sampling is used in business, medical research, social sciences, and many other areas to make inferences about a population based on sample data

 

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