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Abstract Details

Activity Number: 336
Type: Contributed
Date/Time: Tuesday, July 31, 2012 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Education
Abstract - #306019
Title: Bivariate Normal Distribution: A New SOCR Applet
Author(s): Scott Kamino*+ and Ivo D Dinov and Nicolas Christou
Companies: University of California at Los Angeles and SOCR Resource and University of California at Los Angeles
Address: 10933 Rochester Ave., Los Angeles, CA, 90024, United States
Keywords: bivariate normal ; sequential ; Cholesky ; SOCR ; Java applets ; density functions
Abstract:

In this paper we present a new applet of the NSF-funded Statistics Online Computational Research (SOCR) project for the bivariate normal distribution. This 3-D applet allows the user to compute probabilities and quantiles for the joint, marginal, and conditional probability density functions. Sampling from the bivariate normal distribution sequentially and using the Cholesky decomposition method is also available. In addition this Java based applet provides useful visualization tools for greater understanding of the bivariate normal distribution.


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