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Jun 02, 2024
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MATH 437 - Modern Approaches to Data Analysis (4) Nonparametric statistical inference, including methods based on rank and order; resampling, including bootstrap; smoothing histograms, including kernel and smoothing-spines; clustering with logistic and multinomial models, hierarchical clustering and k-means; inference based on posterior distributions, learning and neural networks. (3 hours lecture, 2 hours activity)
Prerequisites: MATH 335 , MATH 439 .
Undergraduate Course not available for Graduate Credit
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