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When using multiple regression, we occasionally find that some subset of the observations is unusually influential. Sometimes these influential observations are relatively far away from the vicinity where the rest of the data were collected. A hypothetical situation for two variables is depicted in Fig. 12-10, where one observation in x-space is remote from the rest of the data. The disposition of points in the x-space is important in determining the properties of the model. For example, point (xi1, xi2) in Fig. 12-10 may be very influential in determining R2, the estimates of the regression coefficients, and the magnitude of the error mean square.

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We would like to examine the influential points to determine whether they control many model properties. If these influential points are bad points, or erroneous in any way, they should be eliminated. On the other hand, there may be nothing wrong with these points, but at least we would like to determine whether or not they produce results consistent with the rest of the data. In any event, even if an influential point is a valid one, if it controls important model properties, we would like to know this, since it could have an impact on the use of the model. Montgomery, Peck, and Vining (2001) and Myers (1990) describe several methods for detecting influential observations. An excellent diagnostic is the distance measure developed by Dennis R. Cook. This is a measure of the squared distance between the usual least squares estimate of based on all n observations and the estimate obtained when the ith point is removed, say, 1i2. The Cook distance measure is 1 1i2

In contrast, Vocabulary, Comprehension, and Similarities are considered good measures of one or more of the following by Bannatyne, Guilford, Rapaport, or Dean: concept formation, judgment, cogni-.

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Clearly, if the ith point is influential, its removal will result in 1i2 changing considerably from the value . Thus, a large value of Di implies that the ith point is influential. The statistic Di is actually computed using

Appropriate solutions are determined by the context, the problem and the forces of the pattern. Note that security patterns are not limited to architectural or design patterns. Depending of the type of the problem, the fundamental solution principle can be at one or more different levels organization, architecture, operations, processes, and so on. Countermeasures are applied to reduce the effect of an attack or threat. Such countermeasures prevention, detection, reaction have different effects on the overall security level.

tion, evaluation, abstract thought, and social comprehension. Indeed, this triad of subtests composes Bannatyne s Verbal Conceptualization category. Nonetheless, Arithmetic is classified by Guilford as a measure of cognition as well as memory, and Vocabulary is categorized by Rapaport as a dual measure of concept formation and memory. Hence, when examiners search for a memory conceptualization split within the WAIS-III Verbal Scale, they must do so with flexibility and with the awareness that most Verbal subtests are complex. Ben s Verbal profile (below) provides a good example of a clear-cut memory reasoning split (conceptual subtests are in bold face).