Population in Statistics

  • Population refers to the entire set of individuals, items, or data points that you are interested in studying. It represents the complete group from which you want to draw conclusions.

Examples

  • All students in a university
  • Every product in a warehouse
  • All residents of a city

Characteristics

  • Every individual has the same probability of being included in the sample.
  • Selection is typically done using random number generators or drawing names from a hat.
  • Sampling Frame: A list or database that includes all members of the population from which the sample is drawn.
  • Sampling Error: The difference between the results obtained from a sample and the actual parameters of the population. It is inherent in the sampling process and can be minimized with proper sampling techniques.
  • Stratified Sampling: A method that divides the population into subgroups (strata) and then randomly samples from each subgroup. This ensures representation across key variables.