A more convenient method of selecting a random sample is to use the

# A more convenient method of selecting a random sample

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A more convenient method of selecting a random sample is to use the identification number of each employee and a table of random numbers such as the one in Appendix B.6. 260 Systematic Random Sampling EXAMPLE A population consists of 845 employees of Nitra Industries. A sample of 52 employees is to be selected from that population. First, k is calculated as the population size divided by the sample size . For Nitra Industries , we would select every 16th (845/52) employee list. If k is not a whole number , then round down. Random sampling is used in the selection of the first name. Then, select every 16 th name on the list thereafter. Systematic Random Sampling: The items or individuals of the population are arranged in some order. A random starting point is selected and then every k th member of the population is selected for the sample. 262
Stratified Random Sampling Stratified Random Sampling: A population is first divided into subgroups, called strata, and a sample is selected from each stratum. Useful when a population can be clearly divided in groups based on some characteristics Suppose we want to study the advertising expenditures for the 352 largest companies in the United States to determine whether firms with high returns on equity (a measure of profitability) spent more of each sales dollar on advertising than firms with a low return or deficit. To make sure that the sample is a fair representation of the 352 companies, the companies are grouped on percent return on equity and a sample proportional to the relative size of the group is randomly selected. 262 Cluster Sampling Cluster Sampling: A population is divided into clusters using naturally occurring geographic or other boundaries. Then, clusters are randomly selected and a sample is collected by randomly selecting from each cluster. Suppose you want to determine the views of residents in Oregon about state and federal environmental protection policies. Cluster sampling can be used by subdividing the state into small units— either counties or regions, select at random say 4 regions, then take samples of the residents in each of these regions and interview them. (Note that this is a combination of cluster sampling and simple random sampling.) 263
Methods of Probability Sampling z The sampling error is the difference between a sample statistic and its corresponding population parameter.

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• Spring '11
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