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Unformatted text preview: MIDTERM TWO CHAPTER 7 Why a sample instead of a census? • Less time consuming • Less costly to administer • Less cumbersome and more practical Sampling frame • A listing of items that make up the population • Frames are data sources such as population lists, directories, or maps • Inaccurate or biased results can result if a frame excludes certain portions of the population • Using different frames to generate data can lead to dissimilar conclusions Samples • Non-probability samples- items included are chosen without regard to their probability of occurrence o Judgment- you get the opinions of preselected experts in the subject matter o Convenience- items are selected based only on the fact that they are easy, inexpensive, or convenient to sample • Probability samples o Simple random Every individual or item from the frame has an equal chance of being selected Selection may be with replacement or without replacement Samples obtained from table of random numbers or computer random number generators May not be a good representation of the population’s characteristics o Systematic Decide on sample size: n Divide frame of N individuals into groups of k individuals: k=N/n Randomly select one individual from the first group Select every kth individual thereafter May not be a good representation of the population’s characteristics o Stratified Divide population into two or more subgroups (strata) according to some common characteristic A simple random sample is selected from each subgroup, with sample sizes proportional to strata sizes Samples from subgroups are combined into one Common technique for sampling voters across socio-economic or racial lines Ensures representation of individuals across the entire population o Cluster Population divided into several “clusters”, each representative of the population A simple random sample of clusters is selected All items in the selected clusters can be used, or items can be chosen from a cluster using another probability sampling technique A common example- exit polls More cost effective Less efficient (need a larger sample to acquire the same level of precision) Types of Survey errors • Coverage error or selection bias- exists if some groups are excluded from the frame and have no chance of being selected • No-response error or bias- people who do not respond may be different from those who do not respond • Sampling error- variation from sample to sample always exist • Measurement error- due to weaknesses in question design, respondent error, and interviewer’s effects on the respondent (“Hawthorne Effect”) Sampling Distributions- a theoretical probability distribution of a random variable (all of the possible values of a statistic, like the sample mean or sample proportion) that results from taking all possible random samples of a given size from a given population • Three amazing facts: if a random sample of size n is taken from a population...
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This note was uploaded on 03/28/2012 for the course GEN BUS 303 taught by Professor Mullins during the Spring '08 term at Wisconsin.
- Spring '08