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Sampling

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Sampling. Sampling. Probability Sampling (Scientific) Non Probability Sampling. Non Probability Sampling. Accidental, Haphazard or Convenience Sampling Purposive Sampling Modal Instance Sampling Expert Sampling Quota Sampling Heterogeneity Sampling Snowball Sampling . An Example.

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Sampling

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  1. Sampling

  2. Sampling • Probability Sampling (Scientific) • Non Probability Sampling

  3. Non Probability Sampling • Accidental, Haphazard or Convenience Sampling • Purposive Sampling • Modal Instance Sampling • Expert Sampling • Quota Sampling • Heterogeneity Sampling • Snowball Sampling

  4. An Example • We want to know what proportion p of the adults in the U.S. voted in the last election. p is a parameter of the population. • Unless we ask every adult, we won’t know the value of p. • We can however take a small sample and use the result to estimate the proportion.

  5. We take a “scientific” sample of 1700 adults and ask them if the voted in the last election. 795 say the have voted. • p = 795/1700 0.468 or roughly 47% • We could then say that 47% of the adult population voted in the last election. • We need say how confident we are in this estimate and what the margin of error is.

  6. Quick Estimate for Margin of Error for 95% Confidence Level • where n is the sample size. • In our example the margin would be • or roughly 2.4%

  7. Confidence Statement • In this example we would say something like: We are 95% confident that 47% of the adults voted in the last election with a margin of error of 2.4%

  8. What does this confidence statement mean? • It means that if we were to repeat the sample many times that 95% of the time the results would be within 2.4% of the actual population proportion.

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