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If X and Y are independent, but not necessarily normal, and if the distribution of either X or Y is symmetric, then, clearly, C ( X , Y ) = C*( X . Y ) = 0. Now let S,(X) and Cn(X,Y ) be the finite sample versions based on ( X I , y l ) , . . . (x,. yn). We can expect that the asymptotic distribution of &[Cn(X, Y ) - C ( X , Y ) ]will be normal, but already for a normal parent distribution we obtain some quite complicated expressions. For a nonnormal parent, the situation seems to become almost intractably messy. This approach has another and even more serious drawback: when it is applied to the components of ap-vector X = ( X I , . . . , Xp), it does not automatically produce a positive definite robust correlation or covariance matrix [ C ( X i ,X J ) ] , and thus these matrices may cause both computational and conceptual trouble (the shape ellipsoid may be a hyperboloid!). The schemes proposed by Devlin et al. (1975) to enforce positive definiteness would seem to be very difficult to analyze theoretically. There is an intriguing and, as far as I know, not yet explored variant of this approach that avoids this drawback. It directly determines the eigenvalues X i and eigenvectors u, of a robust covariance matrix: namely find that unit vector u1 for which XI = S ( U T X ) is maximal (or minimal), then do the same for unit vectors u2 ~ orthogonal to u1, and so on. This will automatically give a positive definite matrix.
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Part IV: Creating and Using Libraries
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There are a couple of hard and fast rules that Windows Vista requires you follow before you can even consider using a dynamic disk over a basic disk. You cannot install Windows Vista on a dynamic disk; however, you can extend the volume in order to do so. Extending a volume is simply incorporating unused disk space into the volume without losing or compromising data. Dynamic disks cannot be used on portable computers (laptops), on USB or FireWire (IEEE 1394) disks or other removable disks, or disks using SCSI busses. In other words, you need to use a desktop computer with a standard hard drive.
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If you experimented with the model at FlawOfAverages.com, you would have discovered that when the chance of getting caught reaches 42 percent you should just take the Stick in the Eye and be done with it (see Figure 14.4).
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The electrodeposited (TlBi)1.1Sr1.6Ba0.4Ca2Cu4Ox (TBSBCCO) precursor lms were obtained by co-electrodeposition of the constituent metals using nitrate salts dissolved in dimethyl sulfoxide (DMSO) solvent. A typical electrolytebath composition for the TBSBCCO lms consisted of 1-g TlNO3, 1-g Bi(NO3)3 5H2O, 12.6-g Sr(NO3)2, 11.5-g Ba(NO3)2, 6.8-g Ca(NO3)2 4H2O, and 2.3-g Cu(NO3)2 6H2O dissolved in 390-mL DMSO solvent. The substrates were single-crystal LaAlO3 (LAO) coated with 300 of Ag. The nal lm thicknesses were increased either by increasing the deposition time or by multilayer deposition. Although the lm thickness increases with longer deposition time, the lm morphology tends to be poor, as shown in Fig. 7.9. A two-layer technique that used two layers of TBSBCCO lms, with an intermediate layer of Ag, improved the lm uniformity and morphology, as shown in Fig. 7.10. The deposition process for the multiple layer is as follows: (1) Single-crystal substrates are coated with 300 of Ag; (2) TBSBCCO lms (0.4 1.3 m) are prepared by electrodeposition (ED) on Ag/LAO; (3) 300 of Ag are deposited on ED-TBSBCCO/Ag/LAO; (4) the second layer of TBSBCCO is electrodeposited (0.4 1.3 m) on Ag/ED-TBSBCCO/Ag/LAO; and (5) the complete two-layer system is reacted.
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Custom power supplies vary in one respect or another from the AT and ATX standards.
Symmetric digital subscriber line (SDSL): SDSL provides a constant upload and
Figure 13-9: The Application Removal Completed dialog box.
TableA
he Flaw of Averages describes a set of common avoidable mistakes in assessing risk in the face of uncertainty. It helps explain why conventional methods of gauging the future are so wrong so often, and is an accessory to the recent economic catastrophe. Once grasped, these ideas can lead recent us to more effective forecasting and decision making. Traditionally, these topics have been the domain of probability and statistics. Although I will assume no prior knowledge of these subjects, for those who have had formal training in these subjects, it should take only a few chapters to repair the damage. My perspective no doubt derives largely from my father, Leonard Jimmie Savage. Although well below average on academic scales during his early education, he emerged as a prominent mathematical statistician who collaborated closely with Milton Friedman, among others. One of their students was the founder of modern portfolio theory, Harry Markowitz, who claims that my father indoctrinated him at point blank range with rational expectation theory. Thus I am a child of the University of Chicago School of Economics. Early on it was clear I possessed at least one of my father s traits. I, too, was a below-average student, displaying neither athletic nor academic aptitude. The de ning moment of my high school education came in an after-class conference with my English teacher in my junior year at the University of Chicago Laboratory School. She explained that I was failing the course, but with a monumental effort might achieve a D by the second semester. Then she helpfully explained the underlying problem: The Lab School was for students who would go on to college, which, quite clearly, I would not. Instead she suggested a technical school where I could get practical training as a mechanic or a plumber. She therefore presented me with my rst serious career decision: to work my butt off for a lousy D in English or play my guitar for
Vista lets you get a lot of things done right out of the box. When you install Windows Vista Ultimate, you re also installing a number of useful applications. Before you laugh, let me assure you that most of these applications really are useful; whereas a great deal of the Windows extras in the past have been half-realized, limited throw-ins that nobody really used, you ll probably find yourself actually appreciating the goodies that come with Vista Ultimate.
INDEX Failure: project (reasons for), 41 42, 70 71, 123, 325 326 testing: mean time between failure (MTBF), 373 unrepeatable (one-time anomalies), 370, 380 (see also Anomalies) Failure Modes and Effects (and Criticality) Analysis (FMEA and FMECA), 235, 429 Failure review boards, 276 Farming metaphor, 41 Fast cycle time, 125 127 Fayol, Henri, 19, 31, 32, 255 Feasibility, hardware/software, 430 Feedback, 53, 58 60, 61 Financial management. See Budget Firmware, 376 First article testing, 160 Flowcharts, 66 Focus groups, 148 Follower readiness, 329 Forcing style (power/dominance), 330 Ford, Henry, 69 Ford automobiles, 127, 234, 376 Forms/templates, web site for, 401 402 Formality, 67 68 Formal testing, 160, 369 Frameworks, 11 France, Anatole, 56 Fuller, Thomas, 292 Functional integration, 364 Functional organizations, 45, 169 170 Gantt charts, 29, 211, 215 Gates, control. See Decision gates Gates, Bill, 141, 290, 293 Geostationary Operational Environment Satellite (weather satellite), 126 Glance Management, 55 56, 280 282 Goals, 72, 166, 424, 425 Government, U.S.: Department of Defense (see U.S. Department of Defense (DoD)) Request for Proposal (RFPs), 42, 204 Government Furnished Equipment, Services, and Material (GFE), 215 Government-Off-The-Shelf (GOTS), 162 Graphical languages/tools, 26, 62, 66, 164. See also Systems Modeling Language (SysML); Unified Modeling Language (UML) Grove, Andy, 340 Gruhl, Werner, 90 91 Hall, Rob, 241 Hallucinator, 323 Hardware/software. See also Software: erroneous separation of (Figure 7.7), 106 low-risk solutions, 162 163 Hardware Model Shop Development, 140 Harley Davidson, 372 Harris, Sydney, 56 Harry, Mikel, 252 Hazard analysis, 235 Headcount: report (Figure 16.7), 301 variance, 287 Heating system example, 149, 152, 153, 158 Heinlein, Robert A., 279 Hersey situational leadership model (Figure 18.3), 328 Herzberg, Frederick, 326 327 Hidden enemies, 51, 387 390 Historical templates, generalized, 236 Home building/remodeling, 127 128, 147, 158 House of Quality (quality function deployment, QFD), 140 141, 155 156, 429, 432 Hubble Telescope, 159, 234, 312, 366 Hyundai, 76, 339 340
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