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Variance and Higher Moments - Comprehensive Introduction
Course Topic(s): Probability | Expected Value, variance and higher moments
This page contains the definition of variance and higher moments using the expected value. It contains properties, with proofs, of variance, skew, and kurtosis. It also contains Chebyshevâs inequality. It also has discussions about the variance of special distributions, some of these are given, some the reader is asked to find (answers are given through a small link at the end of the page). It contains links to simulators and directions for the student to use the simulator to observe various properties. Finally, there is a discussion of vector space concepts leading to Minkowskiâs inequality, Lyapunovâs inequality, and convergence.
Resource URL: http://www.math.uah.edu/stat/expect/Variance.html
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Creator(s): Kyle Siegrist
Contributor(s): Kyle Siegrist
This resource was cataloged by Lisa GreenPublisher:
Virtual Laboratories in Probability and Statistics
Resource copyright: Creative Commons
This review was published on October 10, 2012
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