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Figure 18-3 shows another pivot table generated from the bank data. This pivot table uses a page field for the Customer item. In this case, the pivot table displays the data only for existing customers (the user could also select New or All from page field list). Notice the changes in the orientation of the table; branches appear in rows and account types appear in columns. This is another example of the flexibility of a pivot table.

In the following example, a data set relating to diabetes is used to illustrate the process of calculating the coef cients (http://archive.ics.uci.edu/ml/datasets/ Pima Indians Diabetes). Table 4.16 illustrates some of the data used to build the logistic regression model and Fig. 4.30 summarizes the data set. The diabetes variable is used as the response and the other ve variables used as independent variables. The following illustrates the process of calculating the b coef cients. In the rst step, the b coef cients are initialized to an arbitrary value, in this case zero: 2 3 0:0 6 0:0 7 6 7 6 0:0 7 ^ 7 b old 6 6 0:0 7 6 7 4 0:0 5 0:0 The X matrix is constructed from the independent variables, again, with the rst column containing all 1s for calculation of the intercept value. The rst three rows are shown: 2 3 1 97 64 18:2 0:299 21 6 1 83 68 18:2 0:624 27 7 7 X 6 4 1 97 70 18:2 0:147 21 5 ... ... ... ... ... ...

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Write down expressions for <f>/ [P], (y), and show that, for Nt = 0, the eigenvalue solutions are equivalent to the expressions given by Toor 84 Gilliland (1937) derived a solution of the Maxwell-Stefan equations for ternary systems when the flux of component 3 is zero, N3 = 0 Write down expressions for < >,, [P], (y), and show that, for this special case, the eigenvalue solutions are equivalent to the expressions obtained by Gilliland 85 Brocker and Schulze (1991) expounded on Gilliland's solution to the Maxwell-Stefan equations It has long been known that Gilliland's equations are satisfied by more than one set of numerical values for the molar fluxes Brocker and Schulze present criteria for choosing the "correct" set Use the Brocker and Schulze algorithm and determine the three sets of molar fluxes that satisfy Gilliland's equations for, say, Examples 832 and 861.

While hardware detection has much improved in recent years with Linux, there are times when Linux will either not detect a hardware device or improperly identify it. At those times, it helps to know something about tools for listing, modifying, and loading drivers in Linux. Device drivers and modules define the interface between your computer s hardware and the applications you run. Because there are so many potential device drivers that you might need, only the most basic drivers are built into the Linux kernel that you are running. The code needed to handle other devices is added to the kernel, typically when you boot the computer or plug in a removable device, using what are called loadable modules. If your hardware device is properly detected, it will either run from a driver that is built into the kernel or have an appropriate module loaded to handle it (if that module is known and available). If some piece of hardware isn t working when you install Linux (maybe a sound card or Ethernet card, for example), here are some things you can do to figure out what is wrong: 1. Check the boot log. Run the following command to print the kernel ring buffer, which contains information about your bootup process:

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Is the exact matrix solution satisfied by more than one set of numerical values of the fluxes 86 The eigenvalue solutions are also valid for two component systems where all matrices are of order one Simplify the eigenvalue solutions for mass transfer in binary systems when a Nt = 0 b N2 = 0.

Table 2.4 Variables and Data Types Identified for the Problem Statement VARIABLE NAME reg_no name dob add city home_phno score1 score2 avg_score DATA TYPE String String String String String String Integer Integer Float DESCRIPTION Registration number Student name Date of birth Address City Home phone number Score in first subject Score in second subject Average score