Research and Expertise
Research and Expertise
The Center for Statistical Research & Methodology focuses on applying and developing new methods in the following eight areas of statistical research.
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Missing Data & Observational Data ModelingMissing data and observational data modeling methods are used to compensate when some or all of the data are not captured for some responding units.
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Record Linkage & Machine LearningRecord linkage and machine learning methods are used for matching or linking records among various data sets.
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Small Area EstimationSmall area estimation methods provide reliable data products for finer geographic levels and subpopulations when sample sizes for these levels are insufficient.
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Spatial Analysis & ModelingSpatial analysis and modeling methods are used to develop descriptive statistics, build models, and predict outcomes using geographically referenced data.
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Sampling Estimation & Survey InferenceSampling estimation and survey inference methods are used for taking sample data and making valid inferences about populations of people or businesses.
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Time Series & Seasonal AdjustmentSeasonal adjustment methods are used to monitor activity over time and to remove a component of a time series that reveals a seasonal effect in the data.
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Experimentation, Prediction, & ModelingExperimentation, prediction, and modeling methods are used to build models and design experiments to answer questions related to testing.
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Simulation, Data Science, & VisualizationSimulation and data science methods are used to build models and to carry out computer simulations designed under realistic data collection conditions.
Page Last Revised - February 27, 2023