Essentials of Probability and Statistical Inference IV OpenCourseWare: Free Undergraduate Statistics Course by Johns Hopkins University
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 |
|---|---|---|
| Yes | Yes | No |
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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