Comparing Random with Non-Random Sampling Methods

Abstract

Although most people doing survey work would prefer to use random methods when drawing their samples, it is rarely practical. Instead they use a method involving every nth member of the population. This study compares the two methods. It was found that as long as the attribute being sampled is randomly distributed among the population the two methods give essentially the same results. However, if the attribute is not randomly distributed among the population the two methods give radically different results. In some instances the every nth method gives much better inferences about the population than do the random methods. In other instances it gives much worse inferences.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1972
Accession Number
AD0748925

Entities

People

  • Anders Sweetland

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Birds
  • Chi Square Test
  • Computer Programs
  • Computers
  • Data Science
  • Families (Human)
  • Information Science
  • Sampling
  • Statistical Samples
  • Statistical Sampling
  • Statistical Tests
  • Surveys
  • United States

Fields of Study

  • Computer science

Readers

  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks