DATA COLLECTION AND SAMPLING TECHNIQUES

DATA COLLECTION AND SAMPLING TECHNIQUES - Divide the...

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DATA COLLECTION AND SAMPLING TECHNIQUES Telephone Surveys, Mail Surveys, Personal Interviews, Online Surveys All different, costs, labor Most expense –personal interviews Cheapest—online surveys Advantages and disadvantages to different methods Like bias when using the internet or mail, not everyone has a mail box or a  computer Random Sampling Random Number Table Whole set of numbers mixed up in not in natural order Close your eyes and just pick the number  The person relates to the number Systematic Sampling k= 2000/50 = 40 if you 2000 subject and you wanted 50 people in the sample line up all the  subjects in a line and then pick like every 40 th  but when you first pick it is random systematic cause its 40 between each person  Stratified Divide your sample into strata (means groups) The point of doing this type is to understand people in different groups Question driven by groups
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Unformatted text preview: Divide the population into groups then the answer becomes clear Still random because you are picking the sample groups randomly Cluster Dividing the sample group into natural groups like people in grades, class groups, Something that is naturally occurring, no one forcing someone to be there Hospital, school, people living in the same town Cluster of people in a natural group Sampling vs. Cluster Sampling- Something your imposing you think is about the sample Cluster something that is natural already there Convenience Bias cause you go to a certain place Cluster vs. Convenience Cluster- even when you pick your group after that you still make sure that the sample is random within the group Convenience just pick somewhere and dont make sure the it is random, like where you at just do it...
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This note was uploaded on 11/07/2011 for the course SPEA-K 300 taught by Professor Wakhungu during the Fall '09 term at Indiana.

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DATA COLLECTION AND SAMPLING TECHNIQUES - Divide the...

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