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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.
McNemar's test is the test for comparing proportions in data involving the paired samples. The test statistic can be given by it is most useful when the data have a symmetri
Hazard plotting is based on the hazard function of a distribution, this procedure gives estimates of distribution parameters, the proportion of units failing by the given time per
Jelinski Moranda model is t he model of software reliability which supposes that failures occur according to the Poisson process with a rate decreasing as more faults are diagnos
#how to analyse data
Uncertainty analysis is the process for assessing the variability in the outcome variable that is due to the uncertainty in estimating the values of input parameters. A sensitivit
Complier average causal effect (CACE): The treatment effect amid true compliers in the clinical trial. For the suitable response variable, the CACE is given by the difference in o
Profile plots is a technique of representing the multivariate data graphically. Each of the observation is represented by a diagram comprising of a sequence of equispaced vertical
The more effective display than a number of other methods or techniques, for instance, pie charts and bar charts, for displaying the quantitative data which are labeled. An instanc
historigrams and histogram
Probability judgements : Human beings often require assessing the probability which some event will occur and accuracy of these probability judgements often determines success of o
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