chapter 1: the nature of statistics 1.4 other sampling designs
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Chapter 1: The Nature of Statistics
1.4Other Sampling Designs
Drawbacks to simple random sampling
• May fail to provide sufficient coverage when information about subpopulations is required
• May be impractical when the members of the population are widely scattered geographically
Systematic Random Sampling
• Step 1– Divide the population size by the sample size and round the
result down to the nearest whole number, m
• Step 2– Use a random-number table (or a similar device) to obtain a
number, k, between 1 and m
• Step 3– Select for the sample those members of the population that
are numbered k, k+m, k+2m, …, k+(sample size – 1)m
Systematic Random Sampling
• Easier to execute than simple random sampling
• Usually provides results comparable to simple random sampling
• Only exception…prescence of some kind of cyclical pattern in the listing of the members of the population (male, female, male, female,…)– Relatively rare
Cluster Sampling
• Step 1– Divide the population into groups (clusters)
• Step 2– Obtain a simple random sample of the clusters
• Step 3– Use all the members of the clusters obtained in
Step 2 as the sample
Disadvantage to Cluster Sampling
• Each cluster needs to mirror the entire population– Not usually the case, as members of a cluster are
frequently more homogeneous than the members of the population as a whole
Stratified Random Sampling with Proportional Allocation
• Proportional allocation– Strata are sampled in proportion to their size
• Step 1– Divide the population in subpopulations (strata)
• Step 2– From each stratum, obtain a simple random sample of size
proportional to the size of the stratum (total sample size times stratum size divided by population size)
• Step 3– Use all the members obtained in Step 2 as the sample
Multistage Sampling
• Combining of types of sampling
• Used by pollsters and government agencies
• i.e. Cut up into clusters, then do different kinds of sampling to each cluster
Practice Problems
• P. 21-22
• 1.33 – 1.37
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