Independent random sample
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| − | The term “independent” has a different meaning for sample selection than in the context of variables. Independent sample means simply that selecting one sampling element has no influence on the selection of another sampling element. A counter-example of a non-independent selection would be if one selects one element at random and then takes the neighbor to that element as next sample; this is clearly not independent. Also in [[systematic sampling]] the selection of elements or sampling locations is not independent. | + | The term “independent” has a different meaning for sample selection than in the context of variables. Independent sample means simply that selecting one sampling element has no influence on the selection of another sampling element. A counter-example of a non-independent selection would be if one selects one element at random and then takes the neighbor to that element as next sample; this is clearly not independent. Also in [[systematic sampling]] or [[cluster sampling]] the selection of elements or sampling locations is not independent. |
Independence of sample selection is achieved by randomization for each and every sampling element. | Independence of sample selection is achieved by randomization for each and every sampling element. | ||
[[Category:Introduction to sampling]] | [[Category:Introduction to sampling]] | ||
{{Construction}} | {{Construction}} | ||
Revision as of 18:53, 27 October 2013
The term “independent” has a different meaning for sample selection than in the context of variables. Independent sample means simply that selecting one sampling element has no influence on the selection of another sampling element. A counter-example of a non-independent selection would be if one selects one element at random and then takes the neighbor to that element as next sample; this is clearly not independent. Also in systematic sampling or cluster sampling the selection of elements or sampling locations is not independent. Independence of sample selection is achieved by randomization for each and every sampling element.
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