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SURV 615

Statistical Modeling and Machine Learning I

3 Credits

This is the first course in a two-term sequence in applied statistical methods and machine learning that are the basis in handling complex datasets. The topics covered include: overview on the quantitative research, linear regression, analysis of variance, inference, prediction, model diagnostics and selection and resampling methods. The emphasis will be to understand and apply the methods.

Topics

Topics explicitly listed in official catalogue description

Prerequisites & course information

Restriction: Must be in Survey Methodology (Master's) program; or permission of instructor. Additional Information: Must have basic R Programming skills; and must have completed a two course sequence in probability and statistics; or students who have comparable content may contact the department for permission.

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