Please use this identifier to cite or link to this item: 192.168.6.56/handle/123456789/5438
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dc.contributor.authorPatrick, Dattalo-
dc.date.accessioned2018-10-01T05:54:37Z-
dc.date.available2018-10-01T05:54:37Z-
dc.date.issued2008-
dc.identifier.isbn978-0-19-531549-3-
dc.identifier.urihttp://10.6.20.12:80/handle/123456789/5438-
dc.descriptionThe ultimate goal of sample design is to select a set of elements from a population in such a way that descriptions of those elements accurately portray characteristics of the population (parameters) from which they were selected. Another important goal of sample design is to yield maximum precision (i.e., minimum variance) per unit cost. To achieve these goals, researchers typically rely on probability sampling, in which every element in the population has a known chance of being selected into the sample. Probability sampling allows the chance of an element being selected to be quantified (ideally equal). Probability sampling strategies, through statistical procedures, allow estimates of sampling error to be calculated.-
dc.languageenen_US
dc.language.isoenen_US
dc.publisherOxforden_US
dc.subjectSampling (Statistics)en_US
dc.titleDetermining Sample Size : Balancing Power, Precision, and Practicalityen_US
dc.typeBooken_US
Appears in Collections:Social Work

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