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Sampling and Data: Summary

Module by: Susan Dean, Barbara Illowsky, Ph.D.. E-mail the authors

Summary: This module provides an outline/review of key concepts related to statistical sampling and data.

Note: You are viewing an old version of this document. The latest version is available here.


  • Deals with the collection, analysis, interpretation, and presentation of data


  • Mathematical tool used to study randomness

Key Terms

  • Population
  • Parameter
  • Sample
  • Statistic
  • Variable
  • Data

Types of Data

  • Quantitative Data (a number)
    • Discrete (You count it.)
    • Continuous (You measure it.)
  • Qualitative Data (a category, words)


  • With Replacement: A member of the population may be chosen more than once
  • Without Replacement: A member of the population may be chosen only once

Random Sampling

  • Each member of the population has an equal chance of being selected

Sampling Methods

  • Random
    • Simple random sample
    • Stratified sample
    • Cluster sample
    • Systematic sample
  • Not Random
    • Convenience sample


Samples must be representative of the population from which they come. They must have the same characteristics. However, they may vary but still represent the same population.

Frequency (freq. or f)

  • The number of times an answer occurs

Relative Frequency (rel. freq. or RF)

  • The proportion of times an answer occurs
  • Can be interpreted as a fraction, decimal, or percent

Cumulative Relative Frequencies (cum. rel. freq. or cum RF)

  • An accumulation of the previous relative frequencies

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