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Cluster reduction
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#	Item
91	STRATIFICATION OF PRIMARY SAMPLING UNITS FOR THE CURRENT POPULATION SURVEY USING COMPUTER INTENSIVE METHODS Paul W. Ludington, U.S. Bureau of the Census Washington, DC[removed]I. INTRODUCTION An essential design feature of Add to Reading List Source URL: www.amstat.org Language: English - Date: 2002-09-14 07:19:26 Variance reduction Stratification Cluster analysis Mathematical optimization Search algorithm Statistics Sampling Stratified sampling
92	5 OPTIMIZING THE DESIGN FOR OBTAINING THE DATA This section describes DQO Process Step 7, the last step in the DQO Process. The Add to Reading List Source URL: www.epa.gov Language: English - Date: 2012-04-04 11:49:50 Market research Survey methodology Variance reduction Stratified sampling Cluster sampling Simple random sample Sample Random sample Systematic sampling Statistics Sampling techniques Sampling
93	United States Environmental Protection Agency Office of Environmental Information Add to Reading List Source URL: www.epa.gov Language: English - Date: 2011-05-19 15:27:57 Survey methodology Variance reduction Stratified sampling Cluster sampling Sample size determination Sample Simple random sample Random sample Quality assurance Statistics Sampling Market research
94	5 OPTIMIZING THE DESIGN FOR OBTAINING THE DATA This section describes DQO Process Step 7, the last step in the DQO Process. The Add to Reading List Source URL: epa.gov Language: English - Date: 2012-04-04 11:49:50 Market research Survey methodology Variance reduction Stratified sampling Cluster sampling Simple random sample Sample Random sample Systematic sampling Statistics Sampling techniques Sampling
95	5 OPTIMIZING THE DESIGN FOR OBTAINING THE DATA This section describes DQO Process Step 7, the last step in the DQO Process. The Add to Reading List Source URL: www.epa.gov Language: English - Date: 2012-04-04 11:49:50 Market research Survey methodology Variance reduction Stratified sampling Cluster sampling Simple random sample Sample Random sample Systematic sampling Statistics Sampling techniques Sampling
96	CLUSTERING-BASED WIND POWER SCENARIO REDUCTION TECHNIQUE J. Sumaili1, H. Keko1, V. Miranda1, A. Botterud2 and J. Wang2 1 Instituto de Engenharia de Sistemas e Computadores do Porto (INESC Porto) Add to Reading List Source URL: www.pscc-central.org Language: English - Date: 2011-10-28 06:45:41 Wind power Wind power forecasting Cluster analysis Uncertainty Randomness Normal distribution Scenario Statistics Mesoscale meteorology Wind
97	SPA 27 RCRA REVISION CHECKLIST 213 Burden Reduction Initiative 71 FR[removed]April 4, 2006 (RCRA Cluster XVI, HSWA/Non-HSWA) Add to Reading List Source URL: www.epa.gov Language: English - Date: 2012-04-04 11:22:11
98	[removed]Calendar of Activities San Luis Obispo County Community College District[removed]Integrated Planning Manual Month Board of Trustees Add to Reading List Source URL: www.cuesta.cc.ca.us Language: English - Date: 2012-09-01 11:14:54 Development Poverty Reduction Strategy Paper Cluster
99	[removed]Calendar of Activities San Luis Obispo County Community College District[removed]Integrated Planning Manual Month Board of Trustees Add to Reading List Source URL: www.cuesta.cc.ca.us Language: English - Date: 2012-09-01 11:15:45 Cluster Poverty Reduction Strategy Paper
100	Microsoft Word - Martin_Supplement_Final.doc Add to Reading List Source URL: www.sandia.gov Language: English - Date: 2013-12-09 16:26:41 Bioinformatics Dimension reduction Self-organizing map Cluster analysis Boolean network Gene regulatory network K-means clustering Consensus clustering Statistics Neural networks Networks