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In this chapter, a section on the principles of graphics design and graph construction is initially presented. The next section looks at tables, an old and re ned graphical form. The next three sections focus on graphical visualization tools for quantitative data. These tools are classi ed by the number of variables they display, and tools for one variable (univariate data), two variables (bivariate data), or many variables (multivariate data) are discussed. The sections on quantitative data are followed by a section on tools to visualize groups of observations. Finally, there is a section that discusses techniques for interacting with data visualizations to explore the data. Data graphics and visualization tools can be easily found in print or on the internet. Many are examples of how not to communicate your statistical analysis or results, but some deserve careful study. Those commonly used by data analysts are included, in addition to some that are not well known but are effective in niche areas or written about by well-known statisticians and scientists: John Tukey, William Cleveland, Edward Tufte, Howard Wainer, and John Weinstein. These less wellknown graphics illustrate certain design principles and provide examples from speci c application areas of how easily visualization can reveal structure hidden within data or generate ideas for new designs.

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in the dollar by two months. While the direction of interest rates is important to the dollar, it's also useful to monitor the relationship between short- and long-term rates (the yield curve). Having considered interest rate yields, let's turn the picture around now and compare the dollar trend to interest rate futures, which use prices instead of yields.

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If the privacy of the information that is being transmitted between a client application and the ENUM service (first or second level) is compromised, then registrant-sensitive information such as the registrant s username and password, could be obtained by a malicious intruder. The DNS system must be able to prevent eavesdropping attacks.

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all three component sliders for that color (see Figure 4 53). Again, click the All button to see all the controls at once. B&W: when working on a black and white image you can adjust the brightness of the original color components of the photo here, resulting in different grayscale conversions (see Figure 4 54).

11

consumption. Service levels can generally be established into a small number of narrowly de ned offerings, based upon the metrics by which a business unit has recoverability. The metrics are not communicated in IT terms, such as server platform, tape or disk technology, SAN/NAS and so on, but rather in simple terms that quantify the expectations for data recovery. For example, one could establish a simple four-tier hierarchy, which offers platinum, gold, silver and bronze services. An example of service levels is shown in Table 1.1. By establishing clear SLAs and monitoring delivery against these commitments, the operation can be properly funded by more responsible business unit owners. Also, the underlying technology infrastructure can be better managed and upgraded as needed to allow the storage group to deliver on its commitments to the business units.

36 DIFFERENTIATED SERVICES ARCHITECTURE There are three major standardized alternatives to support QoS enforcement for multimedia applications: the IntServ architecture, the differentiated services (DiffServ) architecture, and MPLS This section presents DiffServ [8], a coarse-grained approach providing QoS to aggregated traffic This initiative has been standardized in IETF 361 Goals and Basics The main idea of the DiffServ architecture initiative is to provide differentiated services to an aggregate of flows in an IP network In DiffServ, flows are not treated individually but are considered in groups In effect, only a few services or behaviors are instantiated at network nodes and, as such, user s flows must be treated in aggregates if they are to to receive the available services It is expected that DiffServ will support a large number of user flows, thus allowing this solution to adequately support QoS in very large networks, such as the Internet.

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