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When only the ordinal aspects of data are considered, we have statistical methods in which the statistical and verbal conclusions are very close. Many parametric models are now available for testing highly speci c parametric hypotheses. If a researcher has a carefully planned hypothesis that ts into the framework of a highly parametric model, then he or she should use such a model. However, we very often have more loosely formulated hypotheses and use the highly parametric models as a default. There usually is some sort of Procrustean translation of the original research ideas into questions that t with the sophisticated models. The problem is that an analysis based on a highly parametric model may not provide answers that are tting for the researcher s original questions. We have given a number of reasons that ordinal statistics provide results that are consistent with common types of research questions. The added bene t is that the conclusions and inferences from the ordinal methods are valid under a wide variety of conditions. Furthermore, the results are unchanged under monotonic transformations: They generalize to scores of latent variables as well as observed ones. There are SPSS macros and Fortran programs available for a number of the methods described in this chapter. These may be accessed through the website of J. D. Long, http://education.umn.edu/edpsych/Faculty/long.html. APPENDIX: COMPUTING THE ESTIMATED VARIANCE OF ta Here we illustrate the computation of Est[var(ta )] for the raw data in Table 25.1. The last section of Table 25.1 shows the 2 calculation of the tihxy , tihxy , and ta that are required to compute Equations 25.31 and 25.32, and nally, the estimated variance of Equation 25.30. Using the information from Table 25.1, Equation 25.32 is computed as 2 st2 = ihxy =

In Fig. 11.6 we consider the 10% outage5 capacity and cutoff rate as a function of the SNR 10 log10 Es =N . Again we note the close similarity 0 between the UWB channel models and the i.i.d. Rayleigh fading channel with lognormal shadowing. A comparison of the capacity with the corresponding cutoff rate curves indicates that decent gains of 2.5 3 dB in power ef ciency can be anticipated by the application of more powerful capacity approaching codes such as Turbo or RA codes instead of the convolutional codes proposed in [2 4], which usually perform in the vicinity of the cutoff rate. We will return to this issue in Section 11.7.

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If you have a simple one-word password like computer, a high-tech thief could crack it in mere minutes. If you make the password more robust by adding numbers like computer33 it might take the thief an extra 10 minutes to crack it. If your password is even more complex like comPut3r55@$ the thief would have to work around the clock for days on end before he could come close to cracking it. Your password should have a minimum of six digits, with at least three of the following: lowercase letters, uppercase letters, numbers, and special characters. The easiest way to create a strong password is to develop a pass-phrase, which is a sentence you can easily remember. Use the rst letter of each word in the pass-phrase to create a password. For example, the pass-phrase Honk if you like computer geeks becomes the password hiylcg. To make it even stronger, use a combination of upper and lowercase letters, numbers, and special characters that look like actual letters. For example, hiylcg can be changed into h1yLc&. For even stronger protection, change your passwords every six months.

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Comprehensive coverage on the topic of Web services is impossible within the constraints of one book chapter. Web services are a highly volatile technical domain, and any complete treatment will both read like a Tolstoy novel and soon be outdated. Web services are an amalgamation of many detailed protocols some leveraged by Web services and some created speci cally for Web services. Advocates stress that the whole value of Web services exceeds the sum of these protocols. Web services describe the interactions between network-accessible, runtime components, assembled to create distributed applications. Web services strike a sophisticated balance between the desirable, yet con icting, goals of system extensibility and application interoperability. Web services diverge from the traditional Web in that the interactions contain application-customized, function-oriented data rather than presentation-oriented data universally understood by any browser. From a software engineering perspective, Web services open the way toward more ef cient and effective software application development through component reuse and the sharing of runtime resources. 14.1.1 Web Services De ned There exists a broad movement by the information technology (IT) industry to expand the existing World Wide Web (Web) from a server-to-user interaction model to an application-to-application interaction model. This overall goal is to extend the Web from an information-oriented system to a service-oriented,

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