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Lecture 8
Comm. 88
October 21, 2008
I.
Sampling
A. Representative Sampling (probability sampling)
1.
Representative because everyone in population has equal chance
of being included in sample. (Generalize)
2.
How representative?
B. Sampling error:
1.
Sample data will be slightly different from population because
of chance
alone.
2.
Estimate this statistically (margin of error) [depends on how
confident you want to be, typically 95%]
3.
Reduced by
a.
More homogeneous population
b.
Larger sample size
C. Systematic Error (Sampling Bias):
1.
Systematically overor underrepresent certain segments of
population.
2.
Caused By:
a.
Improper weighting; very low response rate.
b.
Using nonrepresentative sampling methods.
II.
Representative Sampling Techniques
A. Simple Random Sampling
1.
Select elements randomly from population
a.
Listed Population: random #’s table
b.
Phones: randomdigit dialing
B. Systematic Sampling (a.k.a systematic random sampling)
1.
From a list of the population, select every “nth” element.
2.
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 Spring '10
 klein

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