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combination of the variables accounts for more variability than that of any other conceivable linear combination It has maximized the variance Var(Y1 ) = e1 e1 As we suspected from the matrix plot and the correlation matrix, there is evidence that total rooms, total bedrooms, population, and households vary together Here, they all have very high (and very similar) component weights, indicating that all four variables are highly correlated with the rst principal component Let s examine Table 13, which shows the eigenvalues for each component along with the percentage of the total variance explained by that component Recall that result 3 showed us that the proportion of the total variability in Z that is explained by the ith principal component is i /m, the ratio of the ith eigenvalue to the number of variables Here we see that the rst eigenvalue is 3.

901, and since there are eight predictor variables, this rst component explains 3901/8 = 48767% of the variance, as shown in Table 13 (allowing for rounding) So a single component accounts for nearly half of the variability in the set of eight predictor variables, meaning that this single component by itself carries about half of the information in all eight predictors Notice also that the eigenvalues decrease in magnitude, 1 2 m , 1 2 8 , as we noted in result 2 The second principal component Y2 is the second-best linear combination of the variables, on the condition that it is orthogonal to the rst principal component Two vectors are orthogonal if they are mathematically independent, have no correlation, and are at right angles to each other.

Marshalling The collection of techniques capable of converting parameters into a data stream, usually to support RMI, RPC, or Messaging the opposite of unmarshalling Message A data structure or textual stream representing content sent from one COS instance to another Middleware Any additional software used to bridge the gap (translate or hide differences) between COSs Platform A set of software that provides a well-de ned set of operations, facilities, and functionality that serves as the foundation for components, subsystems, and other software that runs on top of the platform Remote Method Invocation (RMI) A remote execution technique based on objectoriented method invocation (calls) Remoting The collection of techniques used to perform any remote functions including remote execution and messaging Servlet A piece of software contained, deployed, and executed within the Web Container that can act as an intermediary between the EJBs and clients that are web-aware but not J2EE-aware.

The second component is derived from the variability that is left over once the rst component has been accounted for The third component is the third-best linear combination of the variables, on the condition that it is orthogonal to the rst two components The third component is derived from the variance remaining after the rst two components have been extracted The remaining components are de ned similarly..

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The following example retrieves data from an Access database named budget.mdb. This database contains one table (named Budget), and the table has seven fields. This example retrieves the data in which the Item field contains the text Lease and the Division field contains the text N. America. The qualifying data is stored in a Recordset object, and the data is then transferred to a worksheet (see Figure 20-10).

sat down, he told me There was so much riding on this interview, and the air in the room was sti ing The dean sat there, behind his desk, with my transcript in his hands, and said nothing for a moment or two Finally, he looked me right in the eyes, held up my transcript, and said, You know, I ve seen better grades than this before I caught my breath, looked right back at him, and said, So have I So have I Then we kept talking At the time, I didn t understand Sig s candor with the dean It seemed foolhardy, given his overall level of quali cation Later, I came to recognize how extraordinary was this simple act Sig got accepted, and he is now a distinguished assistant professor at University of California, San Francisco s department of orthopedic surgery.

He aced his interview in large part because he was simply honest when the situation and the expectations in the room screamed at him to be otherwise He didn t say, Well, let me tell you, my mom was sick, so I took this semester off and my GPA dropped He offered no excuses, no puffery, no lies, but simply acknowledged that he, too, had seen better grades Most people in Sig s situation applying for a new position, whether in a school or with a company portray themselves as something they are not They succumb either to the pressure of being on the spot and feeling like they need to say the right thing to please their superior or the pressures of the old get-ahead-by-any-meansnecessary culture This is easy to understand Nowhere in business are you more vulnerable than when you are trying to nd a job.