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Sampling Algorithms for Evolving Datasets Rainer Gemulla Defense of Ph.D. Thesis 20.10.2008

Sampling Algorithms for Evolving Datasets Rainer Gemulla Defense of Ph.D. Thesis 20.10.2008

Faculty of Computer Science, Institute of System Architecture, Database Technology Group. Sampling Algorithms for Evolving Datasets Rainer Gemulla Defense of Ph.D. Thesis 20.10.2008. Application Level ( external ). Clustering Find similar groups Ofter superlinear in input size

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491 views • 35 slides
Preparing the Sample

Preparing the Sample

Preparing the Sample. What is a sample?. The target population, defined by each site, is the population to which the results of the survey should be applicable. A sample is a carefully selected subset of the target population. Why select a sample of the target population?.

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659 views • 29 slides
California

California

California. For-Hire Review December 2008. Logbooks. Potential to provide an effort census, but not currently used for effort estimation. Logbook response is unreliable. Validation does not appear to be done in an organized manner.

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245 views • 14 slides
California

California

California. For-Hire Review December 2008. Logbooks. Potential to provide an effort census, but not currently used for effort estimation. Logbook response is unreliable. Validation does not appear to be done in an organized manner.

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328 views • 14 slides
The Logic of Sampling

The Logic of Sampling

The Logic of Sampling. Nonprobability Sampling. Convenience Sampling Purposive or Judgmental Sampling Snowball Sampling Quota Sampling. The Logic of Probability Sampling. A sample must reflect the same degree of variation as the actual population.

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70 views • 6 slides

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