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BMED-4480: Biomedical Data Science
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< meta property = "og:description" content = "Introduction of multivariate statistical methods to model and analyze recorded data from physiological systems in biomedical engineering. Statistical approaches related to applied multivariate statistics, classification and regression. Associated linear methods include principal component analysis, Fisher discriminant analysis, partial least squares, canonical correlation analysis and their nonlinear counterparts. Descriptive tools include scatter diagrams, Hotelling's T2 statistics and contribution plots. The course has a strong emphasis on biomedical applications." >
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Biomedical Data Science
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BMED-4480
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Introduction of multivariate statistical methods to model and analyze recorded data from physiological systems in biomedical engineering. Statistical approaches related to applied multivariate statistics, classification and regression. Associated linear methods include principal component analysis, Fisher discriminant analysis, partial least squares, canonical correlation analysis and their nonlinear counterparts. Descriptive tools include scatter diagrams, Hotelling's T2 statistics and contribution plots. The course has a strong emphasis on biomedical applications.
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4 credits
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Cross-listed with:
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< a class = "course-pill" href = "BMED-6480.html" > BMED-6480 Biomedical Data Science< / a >
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Prereqs:
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< a class = "course-pill" href = "MATH-2010.html" > MATH-2010 Multivariable Calculus and Matrix Algebra< / a >
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< a class = "course-pill" href = "ENGR-2600.html" > ENGR-2600 Modeling and Analysis of Uncertainty< / a >
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< th class = "spring season-label" > Spring< / th >
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Biomedical Data Science (4c)
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Seats Taken: 7/15
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Biomedical Data Science (4c)
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Seats Taken: 7/15
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Biomedical Data Science (4c)
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Seats Taken: 8/25
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Biomedical Data Science (4c)
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Seats Taken: 6/25
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Biomedical Data Science (4c)
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Seats Taken: 9/25
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