Lecture 8 - Lecture 8 Comm. 88 October 21, 2008 I. Sampling...

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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 over-or under-represent certain segments of population. 2. Caused By: a. Improper weighting; very low response rate. b. Using non-representative sampling methods. II. Representative Sampling Techniques A. Simple Random Sampling 1. Select elements randomly from population a. Listed Population: random #’s table b. Phones: random-digit 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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Lecture 8 - Lecture 8 Comm. 88 October 21, 2008 I. Sampling...

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