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The term used for the estimation of the misclassification rate in the discriminant analysis. Number of techniques has been proposed for two-group situation, but the multiple-group situation has rarely been addressed. The easiest procedure is the resubstitution technique, in which the training data are classified using the estimated classification rule and proportion incorrectly placed used as the estimate of misclassification rate. This technique is known to have a large optimistic bias, but it has the benefit that it can be applied to the multigroup problems with no modification required. An alternative technique is the leave one out estimator, in which each of the observation in turn is removed from the data and the classification rule recomputed using remaining data. The proportion improperly classified by the procedure will have reduced bias compared to resubstitution technique. This method can also be implied to the multi group problem with no modification but it has the large amount of variance.
Item-total correlation is an extensively used method for checking the homogeneity of the scale made up of number of items. It is simply the Pearson's product moment correlation c
Confounding: A procedure observed in some factorial designs in which it is impossible to differentiate between some main effects or interactions, on the basis of the particular d
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Omitted covariates is a term generally found in the connection with regression modelling, where the model has been incompletely specified by not including significant covariates.
In a mathematics examination the average grade was 82 and the standard deviation was 5. all students with grade from 88 to 94 received grade of B. if the grade are approximately no
seven questions
Partial least squares is an alternative to the multiple regressions which, in spite of using the original q explanatory variables directly, constructs the new set of k regressor v
Cluster analysis : A set of methods or techniques for constructing a sensible and informative classi?cation of an initially unclassi?ed set of data, using variable values observed
Ignorability : The missing data mechanism is said to be ignorable for likelihood inference if (1) the joint likelihood for the responses of the interest and missing data indicators
An unusual aggregation of the health events, real or perceived. The events might be grouped in the particular region or in some short period of time, or they might happen among the
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