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If the process of examining shared abilities uncovers no hypothesized strengths or weaknesses, then interpret the unique abilities that are presumably measured by significantly high or low subtests. The primary focus for explaining significant discrepancies in a profile should be on shared abilities that link several subtests, especially when these hypothesized strengths and weaknesses are supported by background information, behavioral observations, and supplementary testing. However, at times no hypothesized strengths or weaknesses are apparent after examining the potential shared abilities. Subtest-specific interpretations may then have to be made. The unique abilities are listed in the subtest-by-subtest description of abilities listed in 10 (denoted with an asterisk) and in Table 12.5. Before interpreting a unique ability on a subtest, consider its amount of specificity. Those with ample or adequate amounts of specificity may be interpreted (see Table 10.9 in 10). However, even if a subtest score deviates significantly from the mean and if that subtest has ample subtest specificity, do not automatically interpret the unique ability. Only when all hypotheses involving shared abilities prove useless should an examiner acquiesce to an interpretation of a unique and highly specific strength or weakness. When unique abilities are interpreted, other evidence from background data, behavioral observations, or supplemental testing is needed to support the interpretation of the ability.

(c) Fit a new regression model to these data using x1, x2, x6, and x10 as the regressors Find 99% confidence intervals on the regression coefficients in this new model (d) Compare the lengths of the confidence intervals on 1 and 6 from part (c) with those found in part (a) Which intervals are longer Does this offer any insight about adding the variables x2 and x10 to the model 12-29 Consider the electric power consumption data in Exercise 12-6 (a) Find 95% confidence intervals on 1, 2, 3, and 4 (b) Find a 95% confidence interval on the mean of Y when x1 75, x2 24, x3 90, and x4 98 (c) Find a 95% prediction interval on the power consumption when x1 75, x2 24, x3 90, and x4 98 12-30 Consider the bearing wear data in Exercise 12-7 (a) Find 99% confidence intervals on 1 and 2.

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WAIS-III Interpretive Worksheet that is at the end of this chapter. This worksheet can be photocopied directly from the book, and can be used in conjunction with Examiner Forms 12.1 12.14 that contain the shared abilities for each subtest. For those examiners who benefit from dual modes of processing simultaneous and sequential we have prepared a figure that summarizes the nine interpretive steps and depicts which tier of the WAIS-III hierarchy is addressed with each (see Figure 12.6).

(b) Recompute the confidence intervals in part (a) after the interaction term x1x2 is added to the model Compare the lengths of these confidence intervals with those computed in part (a) Do the lengths of these intervals provide any information about the contribution of the interaction term in the model 12-31 Consider the wire bond pull strength data in Exercise 12-8 (a) Find 95% confidence interval on the regression coefficients (b) Find a 95% confidence interval on mean pull strength when x2 20, x3 30, x4 90 and x5 20 (c) Find a 95% prediction interval on pull strength when x2 20, x3 30, x4 90, and x5 20 12-32 Consider the semiconductor data in Exercise 12-9 (a) Find 99% confidence intervals on the regression coefficients (b) Find a 99% prediction interval on HFE when x1 145, x2 220, and x3 50.

(c) Find a 99% confidence interval on mean HFE when x1 145, x2 220, and x3 50 12-33 Consider the heat treating data from Exercise 12-10 (a) Find 95% confidence intervals on the regression coefficients (b) Find a 95% confidence interval on mean PITCH when TEMP 1650, SOAKTIME 100, SOAKPCT 110, DIFFTIME 100, and DIFFPCT 080 12-34 Reconsider the heat treating data in Exercises 12-10 and 12-24, where we fit a model to PITCH using regressors x1 SOAKTIME SOAKPCT and x2 DIFFTIME DIFFPCT (a) Using the model with regressors x1 and x2, find a 95% confidence interval on mean PITCH when SOAKTIME 100, SOAKPCT 110, DIFFTIME 100, and DIFFPCT 080.

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