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Essentials of Probability and Statistical Inference IV OpenCourseWare: Free Undergraduate Statistics Course by Johns Hopkins University

Published Jan 23, 2009

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For the advanced Math student who needs a free online study aid, Johns Hopkins University's 'Essentials of Probability and Statistical Inference IV:Algorithmic and NonParametic Approaches' could be a useful tool. The course is geared towards undergraduate-level students studying Mathematics or Statistics. If you're looking to study concepts like linear methods of classification and the basics of probability, then read on to find out more about this OpenCourseWare class.

Essentials of Probability and Statistical Inference IV:Algorithmic and NonParametic Approaches: Course Specifics

Degree Level Free Audio Video Downloads
Undergraduate Yes No No Yes

Lectures/Notes Study Materials Tests/Quizzes
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Essentials of Probability and Statistical Inference IV: Algorithmic and NonParametic Approaches: Course Details

You'll need a firm grasp of calculus and statistics to keep up the material presented in 'Essentials of Probability and Statistical Inference IV: Algorithmic and NonParametic Approaches.' This advanced, undergraduate-level Math class offered by Johns Hopkins University and taught by Rafael Irizarry is intended to give Math majors an in-depth understanding of new methods to investigate and draw conclusions from data. Course topics covered by the downloadable lecture notes include a review of important mathematical concepts, regression and prediction methods, linear regression, linear classification and kernel methods.

This free OpenCourseWare includes a syllabus, course schedule and six sets of lecture notes. If you'd like to learn more, visit the advanced statistics and probability course page.

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