stat341 / CM 361: Difference between revisions
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==Topics== | ==Topics== | ||
<big>[[Monte Carlo methods]]</big> | <big>[[Monte Carlo methods]]</big> | ||
<big>[[Computational inference]]</big> | <big>[[Computational inference]]</big> | ||
<big>[[Data partitioning and resampling]]</big> | <big>[[Data partitioning and resampling]]</big> | ||
<big>[[Numerical methods in statistics]]</big> | <big>[[Numerical methods in statistics]]</big> | ||
<big>[[Nonparametric probability density estimation]]</big> | <big>[[Nonparametric probability density estimation]]</big> | ||
<big>[[Stastical models and data fitting]]</big> | <big>[[Stastical models and data fitting]]</big> | ||
Revision as of 11:10, 6 May 2009
Computational Statistics and Data Analysis is a course offered at the University of Waterloo, currently being taught by Ali Ghodsi.
Description
Until recently, the use of probabilistic and statistical models has been limited by the complexity of exact inference. However, recent advances from statistics computing science have made many inference tasks practical. This course will provide the fundamentals and algorithms for computational statistics. Examples will be given of applications of these models in different areas.
Topics
Data partitioning and resampling
Numerical methods in statistics