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Isaac Michael "Zick" Rubin (born 1944) is an American social psychologist, lawyer, and author. [1] He is "widely credited as the author of the first empirical measurement of love," [2] for his work distinguishing feelings of like from feelings of love via Rubin's Scales of Liking and Loving.
"Love" is a basic level that concept includes super-ordinate categories of emotions: affection, adoration, fondness, liking, attraction, caring, tenderness, compassion, arousal, desire, passion, and longing. Love contains large sub-clusters that designate generic forms of love: friendship, sibling relationship, marital relationship etc.
The sum of N chi-squared (1) random variables has a chi-squared distribution with N degrees of freedom. Other distributions are not closed under convolution, but their sum has a known distribution: The sum of n Bernoulli (p) random variables is a binomial (n, p) random variable.
Negative correlation can be seen geometrically when two normalized random vectors are viewed as points on a sphere, and the correlation between them is the cosine of the circular arc of separation of the points on a great circle of the sphere. [1] When this arc is more than a quarter-circle (θ > π/2), then the cosine is negative.
A General Theory of Love is a book about the science of human emotions and biological psychiatry written by Thomas Lewis, Fari Amini, Richard Lannon, and psychiatric professors at the University of California, San Francisco, and was first published by Random House in 2000. It has since been reissued twice, with new editions appearing in 2001 ...
The theory of statistics provides a basis for the whole range of techniques, in both study design and data analysis, that are used within applications of statistics. [1] [2] The theory covers approaches to statistical-decision problems and to statistical inference, and the actions and deductions that satisfy the basic principles stated for these different approaches.
In probability theory and statistics, complex random variables are a generalization of real-valued random variables to complex numbers, i.e. the possible values a complex random variable may take are complex numbers. [1] Complex random variables can always be considered as pairs of real random variables: their real and imaginary parts.
To define the Hellinger distance in terms of elementary probability theory, we take λ to be the Lebesgue measure, so that dP / dλ and dQ / dλ are simply probability density functions. If we denote the densities as f and g, respectively, the squared Hellinger distance can be expressed as a standard calculus integral