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- W2220687423 abstract "This chapter examines the practical creation of linear correlation between random variables. The simplest form of relation between two variables is a functional dependence in which to each value of one variable, there corresponds a well-defined value of the other variable. It is assumed that to each set of values of the independent variables, there corresponds a well-defined value of a function. The study of such functional dependence constitutes a part of the calculus. However, there exist relations between physical variables that cannot be attributed to a type of functional dependence. The chapter discusses the dependence between random variables by using the ideas of conditional distribution and conditional expectation. The derivation and study of regression functions are fundamental problems for the analysis of correlational dependence. Two random variables ξ and η are said to be linearly correlated if both the regression functions f(x) and g(y) are linear. In this case, both the regression curves are straight lines and are called the regression lines." @default.
- W2220687423 created "2016-06-24" @default.
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- W2220687423 date "1965-01-01" @default.
- W2220687423 modified "2023-09-25" @default.
- W2220687423 title "LINEAR CORRELATION" @default.
- W2220687423 doi "https://doi.org/10.1016/b978-1-4831-6774-9.50012-7" @default.
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