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Variance and Higher Moments - Comprehensive IntroductionCourse 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 To rate this resource on a 1-5 scheme, click on the appropriate icosahedron:
Creator(s): Kyle Siegrist Contributor(s): Kyle Siegrist This resource was cataloged by Lisa Green Publisher:Virtual Laboratories in Probability and Statistics Resource copyright: Creative Commons This review was published on October 10, 2012
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