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the normalized histogram only, to save space. However, the analyst should not depend on the normalized histograms alone, since these do not display information about the differing densities in the distribution. Figure 7.13 shows the normalized histograms for the following variables, z ln purchase visits, z ln # individual items purchased, z ln total net sales, and z ln # different product classes. All of the relationships show that as the variable increases,

Companies that do little transactional volume should consider using an outsourced service bureau to perform this service.

(10.17)

Crc, the amplitude of the correction of the orbital radius cosine; Crs, the amplitude of the correction of the orbital radius sine; Cic, the amplitude of the correction of the inclination angle cosine; Cis, the amplitude of the correction of the inclination angle sine.

2 i( j)

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and (e) any other nuisance variables such as environmental conditions that have not been controlled. Consider the weight loss of the fth participant in treatment level a2. Suppose that two months after beginning the diet this participant has lost 13 pounds (Y52 = 13). What factors have affected the value of Y52 One factor is the effectiveness of the diet. Other factors are her weight prior to starting the diet, the degree to which she stayed on the diet, and the amount she exercised during the two-month trial, to mention only a few. In summary, Y52 is a composite that re ects (a) the effects of treatment level a2, (b) effects unique to the participant, (c) effects attributable to chance uctuations in the participant s behavior, (d) errors in measuring and recording the participant s weight loss, and (e) any other effects that have not been controlled. Our conjectures about Y52 or any of the other 44 observations can be expressed more formally by a model equation. The classical model equation for the weight-loss experiment is Yi j = where Yi j is the weight loss for participant i in treatment level aj. is the grand mean of the three weight-loss population means. is the treatment effect for population j and is equal to j . It re ects the effects of diet aj. is the within-groups error effect associated with Yi j and is equal to Yi j j . It re ects all effects not attributable to treatment level aj. The notation i( j) indicates that the ith participant appears only in treatment level j. Participant i is said to be nested within the jth treatment level. Nesting is discussed in the section titled Hierarchical Designs. +

A generic call Broadcast(u) performed in Phase 3 is said to Fail to decrease if u v + 2 and yet the status of the channel is COLLISION Succeed in decreasing if u v + 3 and yet the status of the channel is NULL Fail to increase if u v 2 and yet the status of the channel is NULL Succeed in increasing if u v 3 and yet the status of the channel is COLLISION Be good, otherwise More generally, we say that the call Broadcast(u) fails if it fails either to increase or to decrease; similarly, the call Broadcast(u) is said to succeed if it succeeds either to increase or to decrease. Referring to Figure 10.2, the motivation for this terminology comes from the observation that if Broadcast(u) succeeds then, u is updated so that u approaches v. Assume that the call Broadcast(u) is good. Clearly, if such is the case, the double inequality v 2 u v + 2 holds at the beginning of the call. The status of the channel in Broadcast(u) is SINGLE with probability at least n 1 1 1 u 1 2u 2

which is measured in symbols per second. When the discrete alphabet used in the transmission contains only two symbols, M = 2, then it is binary transmission, and the corresponding symbol rate r = rb is the binary signalling rate rb = 1/Tb (bit per second) (5)

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