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Recursive Algorithm for Statistical Analysis of Bivariate Data Using Abstract Data Type Binary Tree

Bivariate data can be defined as a collection of n pairs of data. Bivariate numeric data can be very useful in statistical analysis because it can be used to compute some important statistics, like correlation coefficient, regression analysis parameters, covariace etc. Though the recursive algorithms that will use binary tree to store and manipulate bivariate data will have double recursion, it has become a matter of academic concern to consider how the binary tree can be used to store and manipulate bivariate data. This paper develops novel algorithms for the operations of a binary tree that has two data items at the node, and it uses these novel algorithms to develop novel recursive algorithms that will compute some important bivariate statistics from the bivariate data stored in a binary tree.