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belong to both plans is churn = true, this time by a posterior odds ratio of 0.00004227 = 7.30 0.000005788 The evidence is even more solid in favor of a classi cation of churn = true for these customers, and we did not have to burden ourselves with an assumption about normality. The empirical probability estimation method shown here should be veri ed over a range of margins of error. Above, we found the numbers of records within a margin of error of two records (798 T 802). The reader may verify that that there are eight churn records and three nonchurn records within 5 minutes of the desired 800 minutes, and that there are 15 churn records and ve nonchurn records within 10 minutes of the desired 800 minutes. So the approximate 3 : 1 ratio of churn records to nonchurn records in this area of the distribution seems fairly stable.

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So what happens when the consumer returns the goods to you You had processed an authorization and a settlement and the money has been handed over, and now you have to refund money back to the consumer. This is done by processing a credit. When you do this, your acquiring bank will pass money back to the consumer s credit card. When a consumer requests a refund, only refund back to the same method of payment he or she originally used to pay you. This is an easy scam from fraudsters to purchase goods with credit cards and request credits in cash.

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These are not competing conceptualizations of the same phenomenon as some maintain (eg, Skilling et al, 2002) because they reflect different frames of reference and different areas of inquiry The domain of personality is stylistic variations between people, while social deviance refers to departures from cultural and moral standards (Blackburn, 1988) It.

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conditions of measurement under which the estimate will be obtained Internal Consistency It is also critical to examine the assumption of nonsubstantive facets of error when examining the method of internal consistency as an estimate of reliability Internal consistency is typically measured by splitting the items of a multi-item scale into two parts and determining the correlations between the parts; hence the use of the term split-half reliability to describe this technique Because the approach depends upon the particular split of items involved (eg, correlating odd and even items will not necessarily give the same result as correlating the rst and last halves of items on the scale), estimates of the results of all possible split-half combinations of items can be provided by the K-R 20 formula or by coef cient alpha, the generalized form of K-R 20 for nonbinary items with calculable item variances.

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20 However, the most probable rst implementations will certainly deal with GPS and Galileo, especially in the E1-L1-E2 band for receiver electronics reasons (see 7 for details).

These numbers are a direct function of the average item intercorrelation and the number of items on the scale; higher values for either lead to higher estimates for coef cient alpha Conceptually, coef cient alpha is simply a summary metric of the equivalence of items, and once again any distinctions between items are assumed to re ect random measurement error However, there are problems with assuming (or even desiring) item equivalence Loevinger s classic 1954 article on the attenuation paradox pointed out that high interitem correlations can constrain validity (although they may maximize internal consistency) by narrowing the measurement of complex constructs through a focus upon redundant, albeit valid, variance As noted previously, the paradox is that, while under the assumptions of classical test theory, reliability is considered to be a necessary condition for that sets an upper bound for validity.

Loevinger points out that interitem correlation is not conceptually necessary, and that it can, in fact, lower validity This lowering of validity tends to work through the mechanism of reducing content validity, because highly redundant items cannot capture a broad range of phenomena that might be associated with a complex construct There are other instances in which content validity can be compromised by the assumption of item equivalence One such example is provided by item response theory, whereby items are selected to provide information at differing points on the trait continuum, and thus are speci cally assumed not to be equivalent Internal consistency is also in uenced by the composition of the sample in which it is determined: Item intercorrelation should be lower in samples that are homogeneous on the trait, and higher in heterogeneous.

Handbook of Sensor Networks: Algorithms and Architectures, Edited by Ivan Stojmenovic Copyright # 2005 John Wiley & Sons, Inc.

In the VBE, the Properties window adjusts to display the properties of the selected item (which can be a control or the UserForm itself). In addition, you can select a control using the drop-down list at the top of the Properties window (see Figure 13-4).

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This section was contributed by Samuel Saporta and Don F. Cameron, to whom all correspondence should be addressed.

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