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Lecture 5

Week 5 EC255.docx

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Department
Economics
Course
EC255
Professor
Alex Lun
Semester
Fall

Description
EC255 Week 5 7.1 SAMPLING -Data are gathered from samples and conclusions are drawn about the population as a part of the inferential statistics process -The term census refers to a study of all units of the population of interest -The term sample refers to a study of only a portion of that population Reasons for Sampling 1. The sample can save money 2. It can save time 3. For given resources, the sample can broaden the scope of the study 4. Because the research process is sometimes destructive, the sample can save product 5. If accessing the population is impossible, the sample is the only option Reasons for Taking A Census 1. To eliminate the possibility that by chance a randomly selected sample may not be representative of the population 2. Safety of the consumer -Even when proper sampling techniques are implemented in a study, it is possible that a sample could be selected by chance that does not represent the population Frame -The sample is taken from a population list, map, directory, or other source used to represent the population – this list, map or directory is called the frame -Ideally, a one-to-one correspondence exist between the frame units and the population units -In reality, the frame and the target population are often different -Ex. A feasible frame would be the residential pages of the Montreal telephone book – it would differ from the target population because some families have no telephone -Frames that have over registration contain the target population units plus some additional units -Frames that have under registration contain fewer units than does the target population Random versus Non-random Sampling -In random sampling, every unit of the population has the same probability of being selected into the sample -In non-random sampling, not every unit of the population has the same probability of being selected into the sample -Sometimes random sampling is called probability sampling, and non-random sampling is called non- probability sampling -Non-random sampling methds are not appropriate techniques for gathering data to be analyzed by most o the statistical methods presented in this text Random Sampling Techniques Simple Random Sampling -Each unit of the frame is numbered from 1 to N(N is the size of the population). Next, a table of numbers or a random number generator is used to select n items into the sample. A random number generator is usually a computer program that allows computer calculated output to yield random EC255 Week 5 numbers Stratified Random Sampling -The population is divided into non-overlapping subpopulations called strata. The researcher then extracts a simple random sample from each of the subpopulations -Stratified random samples allow the researcher to study each stratum individually by making sure that even a small stratum of interest is properly represented, and they have the potential
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