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more theory driven and that integrates normative assessment (performance relative to age peers) with ipsative assessment (performance relative to the person s own mean level). This new approach was developed by Flanagan and Kaufman (2004) for the latest version of Wechsler s scales the Wechsler Intelligence Scale for Children: Fourth Edition (WISC-IV; Wechsler, 2003) and is described in depth in their recent book, Essentials of WISC-IV Assessment. The Flanagan-Kaufman approach depends heavily on the merger of the Horn-Cattell and Carroll theories of intelligence (Cattell-Horn-Carroll or CHC theory). This CHC theory-based approach has also been applied to the interpretation of the new Kaufman Assessment Battery for Children Second Edition (KABC-II; Kaufman & Kaufman, 2004) in Essentials of KABC-II

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Figure 6-14 Box plot for compressive strength data in Table 6-2.

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Figure 6-14 presents the box plot from Minitab for the alloy compressive strength data shown in Table 6-2. This box plot indicates that the distribution of compressive strengths is fairly symmetric around the central value, because the left and right whiskers and the lengths of the left and right boxes around the median are about the same. There are also two mild outliers on either end of the data. Box plots are very useful in graphical comparisons among data sets, because they have high visual impact and are easy to understand. For example, Fig. 6-15 shows the comparative box plots for a manufacturing quality index on semiconductor devices at three manufacturing plants. Inspection of this display reveals that there is too much variability at plant 2 and that plants 2 and 3 need to raise their quality index performance. EXERCISES FOR SECTION 6-5

ALTERNATIVE APPROACH TO INTERPRETING THE WAIS-III TABLE A.1 Subtest Composition of the Four WAIS-III and WISC-IV Indexes

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6-42. Exercise 6-13 presented the joint temperatures of the O-rings ( F) for each test ring or actual launch of the space shuttle rocket motor. In that exercise you were asked to nd the sample mean and sample standard deviation of temperature. (a) Find the upper and lower quartiles of temperature. (b) Find the median. (c) Set aside the smallest observation (31 F2 and recompute the quantities in parts (a) and (b). Comment on your ndings. How different are the other temperatures from this smallest value (d) Construct a box plot of the data and comment on the possible presence of outliers. 6-43. An article in the Transactions of the Institution of Chemical Engineers (Vol. 34, 1956, pp. 280 293) reported data from an experiment investigating the effect of several process variables on the vapor phase oxidation of naphthalene. A sample of the percentage mole conversion of naphthalene to maleic anhydride follows: 4.2, 4.7, 4.7, 5.0, 3.8, 3.6, 3.0, 5.1, 3.1, 3.8, 4.8, 4.0, 5.2, 4.3, 2.8, 2.0, 2.8, 3.3, 4.8, 5.0. (a) Calculate the sample mean. (b) Calculate the sample variance and sample standard deviation. (c) Construct a box plot of the data. 6-44. The cold start ignition time of an automobile engine is being investigated by a gasoline manufacturer. The following times (in seconds) were obtained for a test vehicle: 1.75, 1.92, 2.62, 2.35, 3.09, 3.15, 2.53, 1.91. (a) Calculate the sample mean and sample standard deviation. (b) Construct a box plot of the data. 6-45. The nine measurements that follow are furnace temperatures recorded on successive batches in a semiconductor

Andreas L. Opdahl is Professor of Information Systems Development at the Department of Information Science and Media Studies, University of Bergen, Norway. He is the author, co-author or co-editor of more than fifty journal articles, book chapters, refereed archival conference papers and books on multi-perspective enterprise modeling, requirements engineering, information systems architecture, software performance engineering and other areas. He serves regularly as a reviewer for premier international journals and on the program committees of renowned international conferences and workshops, and is a member of IFIP WG8.1 on Design and Evaluation of Information Systems.

WAIS-III WISC-IV Verbal Comprehension Vocabulary Similarities Information Vocabulary Similarities Comprehensive

It is impractical to inspect quality into a product; the product must be built right the rst time. The manufacturing process must therefore be stable or repeatable and capable of operating with little variability around the target or nominal dimension. Online statistical process control is a powerful tool for achieving process stability and improving capability through the reduction of variability.

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