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SONET is based on a synchronous signal comprised of eight-bit octets, which are organized into a frame structure. The frame can be represented by a two-dimensional map comprising N rows and M columns, where each box so derived contains one octet (or byte). The upper left-hand corner of the rectangular map representing a frame contains an identi able marker to tell the receiver it is the start of frame. SONET consists of a basic, rst-level, structure called STS-1, which is discussed in the following. The de nition of the rst level also de nes the entire hierarchy of SONET signals because higher-level SONET signals are obtained by synchronously multiplexing the lower-level modules. When lower-level modules are multiplexed together, the result is denoted as STS-N (STS stands for synchronous transport signal), where N is an integer. The resulting format then can be converted to an OC-N (OC stands for optical carrier) or STS-N electrical signal. There is an integer multiple relationship between the rate of the basic module STS-1 and the OC-N electrical signals (i.e., the rate of an OC-N is equal to N times the rate of an STS-1). Only OC-1, -3, -12, -24, -48, and -192 are supported by today s SONET.

Remember that in these expressions N (i) represents the set of indexes of all the parent symbol nodes connected to the parity check node h i , whereas N (i)\ j represents the same set with the exclusion of the parent symbol node d j . Coef cients Ri0j and Ri1j are then calculated by performing Ri0j = 1/2 1 + Ri j and Ri1j = 1/2 1 Ri j (23) (22)

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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.

0 0

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.

Figure 9-10

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..

The weight-loss data from Tables 1.2 and 1.9 are recasts in the form of an SPF-3 2 design in Table 1.11. The ANOVA for these data is given in Table 1.12. The null hypothesis for treatment B can be rejected. However, the null hypothesis for treatment A and the A B interaction cannot be rejected. The denominator of the F statistic for treatment A [MSBL(A) = 20.1667] is almost twice as large as the denominator for the tests of B and A B (MSRES = 10.8333). A feeling for the relative power of the test of treatment A for the SPF-3 2, CRF-32, and RBF-32 designs can be obtained by comparing their F statistics and p values:

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).

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