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Point scoring is an easy distribution free method which can be used for the prediction of a response which is a binary variable from the observations on several explanatory variables which are also binary in nature. The easiest version of the process, often known as the Burgess technique, operates by first taking the explanatory variables one at a time and then determining which level of each variable is related with the higher proportion of 'success' category of the binary response. The prediction score for any of the individual is then just the number of explanatory variables at the high level (generally only variables which are ' significant' are included in the score). The score thus varies from 0, when all explanatory variables are at low level, to its maximum value when all important variables are at the high level. The goal of the technique is to split the population into risk groups.
The computer programs designed to mimic the role of the expert human consultant. This type of systems are capable to cope with the complex problems of the medical decision makin
we are testing : Ho: µ=40 versus Ha: µ>40 (a= 0.01) Suppose that the test statistic is z0=2.75 based on a sample size of n=25. Assume that data are normal with mean mu and standa
A procedure whereby the collection of multiple sample units are combined in their entirety or in part, to form the new sample. One or more succeeding measurements are taken on the
Regression through the origin : In some of the situations a relationship between the two variables estimated by the regression analysis is expected to pass by the origin because th
Asymmetric proximity matrices : Proximity matrices in which the non-diagonal elements, in the ith row and jth column and the jth row and ith column, are not essentially equal. Exam
moving and semi average method graphical reprsentation
The procedure in which the prior distribution is required in the application of Bayesian inference, it is determined from empirical evidence, namely same data for which the posteri
Histogram is the graphical representation of the set of observations in which class frequencies are represented by the regions of rectangles centred on the class interval. If the f
You have probably noticed by now that some of the statements of necessary and sufficient conditions sound more natural than others. For example it seems more natural to express "We
can you help specify the model for an event study and to interpret the results/
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