Transcript What are the Odds?

What are the Odds?
Sampling Theory and Logic
Let’s Be Realistic…
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It’s unlikely you’ll be in a position to do
much sampling in your daily work
Important to know sampling theory
when consuming research
The Logic of Probability
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The universe and the sample
The theoretical distribution curve (bellshaped curve)
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random distribution about the mean
Mean and standard deviation, true and
sample
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Natural variation of the sample mean
about the true mean
Random Samples
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“Equal chance of being chosen”
Sample size
Simple random sampling
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Random number generation (p. 681)
Systematic random sampling (kth
sampling)
Stratified Sampling
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Breaks the cardinal rule: unequal
chance of being chosen
In social work, interested in minority
opinion
Disproportionate stratified sampling
captures minority voice
“Stratify for variables of interest,
randomize the rest”
Strategies for Stratification
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Divide population into homogeneous
subgroups of interest
Disproportionate stratification
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Sample based on subgroup size: simple
random or systematic (p. 269)
Simple oversampling
Must not generalize to larger population
Gender and Cultural Bias
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“When one group is the norm, the other
group is the deviant”
Systematic vs. random errors
Source of systematic errors
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Population frame bias
Insufficient sample size
Generalization errors – up and down
“Stratify variables of interest, randomize
the rest”
Non-random Sampling
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Convenience or availability sampling
Purposive sampling
Snowball sampling
Quota sampling