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Of course, choosing the most useful variables is a modeling task, which lies downstream of our present phase, the EDA- avored data understanding phase. However, a very rough tool for choosing some useful variables to examine at this early phase is correlation. That is, examine the correlation coef cients for each predictor with the response, and select for further examination those variables that have the largest absolute correlations, say, |r | 0.30. The data miner should, of course, be aware that this is simply a rough EDA tool, and linear correlation with a 0 1 response variable is not appropriate for inference or modeling at this stage. Nevertheless, this method can be useful for paring down the number of variables that would be helpful to examine at the EDA stage. Table 7.4 provides a list of the variables with the highest absolute correlation with the target variable, response. We therefore examine the relationship between these selected predictors and the response variable. First, Figure 7.11 shows a histogram of z ln lifetime average time between visits, with an overlay of response (0 = no response to the promotion). It appears that records at the upper end of the distribution have lower response rates. To make the interpretation of overlay results more clearly, we turn to a normalized histogram, where each bin has the same height, shown in Figure 7.12. Figure 7.12 makes it clear that the rate of response to the marketing promotion decreases as the lifetime average time between visits increases. This makes sense, since customers who visit the store more rarely will presumably be less likely to respond to the promotion. For the remaining variables from Table 7.4, we examine

The analyst needs to understand that just because the effect is found to be statistically signi cant because of the huge sample size, it doesn t necessarily follow that the effect is of practical signi cance The analyst should keep in mind the constraints and desiderata of the business or research problem, seek con uence of results from a variety of models, and always retain a clear eye for the interpretability of the model and the applicability of the model to the original problem Note that the t-test does not give us an idea of how an increase in day minutes affects the odds that a customer will churn Neither does the t-test provide a method for nding the probability that a particular customer will churn, based on the customer s day minutes usage.

(7.67)

Applications are the most prominent kinds of bundles, but they re far from the only bundles on your Mac. Bundles provide a handy general mechanism for keeping a bunch of stuff behind a single icon. Mac OS X uses bundles in various situations that require code to be kept together with images, property lists, and other flotsam. Screen savers, preference panes, Dashboard widgets, frameworks, and application plug-ins are all bundles, each one with some files that have code and others containing data.

Also, desirable attributes of functionally enhanced prebiotics listed by Rastall (2000) are: (1) targeting speci c probiotics (Lactobacillus and/or Bi dobacterium), (2) active at low dosage with lack of side effects, (3) persistence through the colon, (4) protection against colon cancer, (5) enhancement of the barrier effect against pathogens, and (6) inhibition of adhesion of pathogens.

Wire, cable, and ber are well-behaved transmission media, and they display little variability in performance. The radio medium, on the other hand, displays notable variability in performance. The radio-frequency spectrum is shared with others and requires licensing. Metallic and ber media need not be shared and do not require licensing (but often require right-of-way). A major factor in the selection process is information bandwidth. Fiber optics seems to have nearly an in nite bandwidth. Radio systems have very limited information bandwidths. It is for this reason that radio-frequency bands 2 GHz and above are used for PSTN and private network applications. In fact, the U.S. Federal Communications Commission (FCC) requires that users in the 2-GHz band must have systems supporting 96 digital voice channels where bandwidths are still modest. In the 4- and 6-GHz bands, available bandwidths are 500 MHz, allocated in 20- and 30-MHz segments for each radio-frequency carrier. One might ask, why use radio in the rst place if it has so many drawbacks Often, it turns out to be less expensive compared with ber optic cable. But there are other factors such as:

Item 1 (amplitude modulation) is where a carrier is varied in amplitude in accordance with the information baseband signal. In the case of item 2 (frequency modulation), a carrier is varied in frequency in accordance with the baseband signal; and for item 3 (phase modulation), a carrier is varied in its phase in accordance with the information baseband signal. Figure 2.9 graphically illustrates amplitude, frequency, and phase modulation. The modulating signal is a baseband stream of bits: 1s and 0s. We deal with digital transmission (e.g., 1s and 0s) extensively in s 6 and 10. Prior to 1960, all transmission systems were analog. Today, in the PSTN, all telecommunication systems are digital, except for the preponderance of subscriber access lines.

PhPfV 1 Ph(1 PfV)

(18.2)

To learn this, we must turn to logistic regression, which we now carry out, with the results given in Table 410 First, we verify the relationship between the odds ratio for day minutes and its coef cient OR = eb1 = e00112717 = 1011335 101, as shown in Table 410 We = discuss interpreting this value a bit later In this example we have b0 = 392929 and b1 = 00112717 Thus, the probability of churning (x) = e 0 + 1 x /(1 + e 0 + 1 x ) for.