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As noted in the previous section, hypothesis generation can be performed in a linear, sequential, left-brained, scientific manner, which is what the nine-step approach in this chapter and 11 have detailed. However, we are sensitive to individual differences in the way adults may approach the same problem. For some people, the sequential, rule-governed methodology described previously conforms well to their typical processing approach; for others, it is a nightmare. Consequently, we are including an alternative method of hypothesis generation, one that might be preferable to individuals who prefer to rely more on simultaneous, holistic ( rightbrained ) problem-solving strategies. This approach also has sequential components, but it emphasizes configurations of subtests and the simultaneous treatment of two or three tasks at a time while deemphasizing mathematical computations and comparisons. Even the empirical determination of significant strengths and weaknesses in the subtest profile is optional. Only one statistical application is mandatory: After the examiner reaches conclusions about contrasting strengths and weaknesses (e.g., high on visual sequential low on visual spatial), determine whether the difference is statistically significant. The easiest way to make this comparison is

[YB97]

(b) Compare the length of this confidence interval with the length of the confidence interval on mean PITCH at the same point from Exercise 12-33 part (b), where an additive model in SOAKTIME, SOAKPCT, DIFFTIME, and DIFFPCT was used Which confidence interval is shorter Does this tell you anything about which model is preferable 12-35 Consider the NHL data in Exercise 12-11 (a) Find a 95% confidence interval on the regression coefficient for the variable Pts (b) Fit a simple linear regression model relating the response variable wins to the regressor Pts (c) Find a 95% confidence interval on the slope for the simple linear regression model from part (b) (d) Compare the lengths of the two confidence intervals computed in parts (a) and (c) Which interval is shorter Does this tell you anything about which model is preferable.

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The ninth step presented above culminates our step-by-step approach to WAIS-III interpretation that began in 11 and is continued in this chapter. To more easily use these nine steps in clinical practice, we have formulated the

12-5 12-5.1

Verbal Subtest Vocabulary Similarities Arithmetic Unique Abilities Language development Word knowledge Logical abstractive (categorical) thinking Computational skill Quantitative Knowledge (CHC theory) Mathematical Achievement (CHC theory) Quantitative Reasoning (CHC theory) Immediate rote recall Memory span (CHC theory) Range of general factual knowledge Demonstration of practical knowledge Evaluation and use of past experiences Knowledge of conventional standards of behavior Facility with overlearned sequences Working memory Subtest Specificity adequate adequate ample

The residuals from the multiple regression model, defined by ei yi yi, play an important role in judging model adequacy just as they do in simple linear regression. As noted in Section 11-7.1, several residual plots are often useful; these are illustrated in Example 12-9. It is also

J. Yoder, J. Barcalow: Architectural Patterns for Enabling Application Security, in Proceedings of PLoP, 1997

Figure 12-6

Letter-Number Sequencing Performance Subtest Picture Completion Digit Symbol-Coding Block Design Matrix Reasoning

Figure 12-7

patterns [HLF00]. The GoF book [GoF95] mentions the possible use of proxies for distributed systems security. A pattern for a remote secure proxy is given in [Amo01]. Authentication in distributed systems is considered in [Bro99] and [FW03].

Visual recognition without essential motor activity Flexibility of Closure (CHC theory) Psychomotor speed Analysis of whole into component parts Nonverbal concept formation Analogic reasoning Induction (CHC theory) Nonverbal problem solving with no time limit Anticipation of consequences Temporal sequencing Perceptual speed (CHC theory) Speed of visual search Ability to benefit from sensory motor feedback Anticipation of relationships among parts Closure speed (CHC theory)

helpful to plot the residuals against variables not presently in the model that are possible candidates for inclusion. Patterns in these plots may indicate that the model may be improved by adding the candidate variable. EXAMPLE 12-9 The residuals for the model from Example 12-1 are shown in Table 12-3. A normal probability plot of these residuals is shown in Fig. 12-6. No severe deviations from normality are obviously apparent, although the two largest residuals (e15 5.88 and e17 4.33) do not fall extremely close to a straight line drawn through the remaining residuals. The standardized residuals 2MSE ei 2 2 ei

(12-41)

to average the scaled scores for the subtests constituting the strength, and also average the scores for the subtests composing the weakness. If they differ by three points or more (a rule of thumb), the hypothesis is confirmed.

Agent systems is a new area in which security patterns have been applied recently [MGS03]. Layers, one of the fundamental patterns in [POSA1], was re-interpreted as a security pattern in [FP01]. All these patterns are about systems aspects. Enterprise-oriented patterns appeared for the first time at EuroPLoP 2002, including patterns for task-based rights management [EH02] and for a variety of management aspects [Rom02].

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