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Generalized principal components analysis: The non-linear version of the principal components analysis in which the goal is to determine the non-linear coordinate system which is most in agreement with the data configuration. For instance, for the bivariate data, y1,y2, if the quadratic coordinate system is sought, a variable z is defined as given below: with the coefficients being set up so that the variance of z is a maximum amongst all such quadratic functions of y1 and y2.
Interval-censored observations are the observations which often occur in the context of studies of time elapsed to the particular event when subjects are not monitored regularl
A comprehensive regression analysis of the case study London has been carried out to test the 4 assumptions of regression: 1. Variables are normally distributed 2. Linear rel
Described by the leading proponent as 'the conscientious, explicit, and judicious uses of present best evidence in making the decisions about the care of individual patients, and
Bubble plot : A method or technique for displaying the observations which involve three variable values. Two of the variables are used to make a scatter diagram and values of the t
Kolmogorov Smirnov two-sample method is a distribution free technique which tests for any difference between the two populations probability distributions. The test is relied on t
In an experiment, power is a function of 1. The number of variables being measured and the beta level 2. The effect size, internal validity and the beta level 3. The number of part
difference between histogram and historigram
1) Question on the first day questionnaire asked students to rate their response to the question Are you deeply moved by the arts or music? Assume the population that is sampled
Geo statistics: The body of methods useful for understanding and modelling spatial variability in a course of interest. Central to these techniques is the idea that measurements t
The Expectation/Conditional Maximization Either algorithm which is the generalization of ECM algorithm attained by replacing some of the CM-steps of ECM which maximize the constrai
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