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140.754.01
Advanced Methods in Biostatistics IV

Location
East Baltimore
Term
4th Term
Department
Biostatistics
Credit(s)
3
Academic Year
2012 - 2013
Instruction Method
TBD
Class Time(s)
Tu, Th, 10:30 - 11:50am
Lab Times
Tuesday, 10:00 - 10:30am (01)
Thursday, 10:00 - 10:30am (01)
Auditors Allowed
Yes, with instructor consent
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Contact Name
Frequency Schedule
Every Year
Prerequisite

140.751-753

Description
Reviews key topics in modern applied statistics. Extends topics of 140.753 to encompass modern semi-parametric and non-parametric methods. Topics include linear, nonlinear and multivariate smoothing, semi-parametric models for clustered data, measurement error models, and statistical learning techniques such as classification, decision trees, and boosting. Emphasis is given both to rigorous methodological development and to practical data analytic strategies. Computational methods designed for semi-parametric inference are presented and relevant software is discussed.
Learning Objectives
Upon successfully completing this course, students will be able to:
  1. Discuss modern regression tools such as scatterplot smoothing and additive models
  2. apply additive models to public health studies and compare results with those of standard regression models
  3. extend additive models to account for count outcomes and clustering
  4. Discuss multivariate smoothing and applications to medical imaging and noise reduction
  5. discuss measurement error models and their application to epidemiological studies
  6. Discuss statistical and scientific model selection and uncertainty
  7. apply modern statistical learning techniques such as clustering, classification trees and boosting for pattern recognition in complex data sets