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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.
A term which covers the large number of techniques for the analysis of the multivariate data which have in common the aim to assess whether or not the set of variables distinguish
The tabulation of a sample of observations in terms of numbers falling below particular values. The empirical equivalent of the growing probability distribution. An example of such
Bartlett decomposition : The expression for the random matrix A which has a Wishart distribution as the product of the triangular matrix and the transpose of it. Letting each of x
The graph for Partial Autocorrelation Function for RES1 shows that there is no autocorrelation even though there are alternating spikes because they fall inside the 5% significance
Intention-to-treat analysis is the process in which all the patients randomly allocated to a treatment in the clinical trial are analyzed together as representing that particular
Johnson''s Job Sequencing for n jobs and 2 machines
need answers to questions in book advanced and multivariate statistical methods
A standard IQ test has a mean of 98 and a standard deviation of 16. We want to be 99% certain that we are within 8 IQ points of the true mean. Determine the sample size
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
Lagrange Multiplier (LM) test The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1
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