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as variance and standard deviation Excel and Gnumeric have built-in capabilities for advanced statistical functions, including analyses that go far beyond descriptive statistics As of this writing, I am not aware that Calc provides native support for statistical analysis, but extensions are available that allow Calc users to leverage the open source statistical package R, discussed in the next section To my knowledge, the spreadsheet included in Google docs does not support advanced statistical functionality at this time If you use a different spreadsheet application than I have discussed here, you should check to determine which statistical analyses it supports before attempting to use it for advanced analysis in your metrics program Statistical Software For more advanced statistical analysis, a variety of applications go beyond the capabilities of ordinary spreadsheets, and they are designed to be easier and more intuitive to use while you re conducting statistical research As with spreadsheets, both commercial and open source programs are available I have experience with the commercial program Minitab Statistical Software, which is commonly found in business and academic environments and has been developed to be relatively easy to use and to provide advanced analytical capabilities Minitab is not the only product for statistical analysis, but I find it quite usable A well-regarded open source statistical analysis package, R, is extremely powerful and as capable as any commercial package R, however, is not as intuitive as most commercial packages and requires a longer learning curve, especially for users who are accustomed to graphical interfaces and point/click/drag/drop workflows (R functions primarily at a command line interface) R is typically found more often in academia and scientific research institutions than in the average corporate business unit Users of the commercial packages such as Minitab will notice the similarities to spreadsheet interfaces, with the familiar cell format But statistics programs allow a user to access many more analytical functions and visualization techniques easily just by accessing a menu Figure 5-6 shows a graphical display of various descriptive statistics produced in Minitab for the weekly firewall data we have been exploring throughout this section.



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FIGURE 7-16





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You can bring an extraordinary level of improvement and sophistication to your security metrics program by using the full toolbox of descriptive statistics available to you I described basic statistical techniques in the preceding section, and I would encourage you to explore these tools But descriptive statistics address only the immediate data with which you are working You cannot assume that your descriptive findings automatically apply to other areas that you have not observed, or to the same areas you have observed under different circumstances You cannot automatically generalize or predict based on a single data point or data set, although many people often do for a variety of reasons (just look at politicians, for example) To use data to generalize findings into areas for which there is no data, or to predict an outcome based on a limited data set, requires different techniques and analytical methods These methods are referred to as inferential statistics, because they involve

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If you browse by genre, you can look up almost any movie even movies that aren t showing on television right now You can even record a particular movie in the future, should it show up on television For additional options, press the More button If you press the More button while you re looking at a movie in the Movies Guide, a menu appears with these options (see Figure 7-17):

Considering that the cultural and communication frameworks have been established, there is a high readiness factor for the deployment of the

5:

a description, rating, and director You can even find reviews, similar movies, and cast information

Figure 5-6

Record Records the movie with a single click View Large Changes the way movies are displayed View Large shows large previews

company business strategies and aligning those in the functional plans The business cascade is an effective way to engage and mobilize the workforce to complete these plans so that their individual performance can be finalized as well The main focus is to assemble professional and supervisory personnel so they have a common understanding and commitment to the direction, strategies, and major objectives of the company and so they can, in turn, link this information to next-level plans Think of the business cascade as an elevator shaft If you are standing at the bottom, you can look up and see the connections to the other floors In a similar way, the business cascade is a framework in which every person can look up and see the connections to the next level of planning (Exhibit 5-3) This can help create the feeling that every level is critical to the achievement of the company objectives (and every level is)

drawing conclusions or making inferences about something you have not observed on the basis of those things that you have observed At this stage, I want to provide more context to the discussion of techniques and tools provided in this chapter I am not a statistician (I just played one in grad school), a fact that will be obvious to any real statisticians reading this book I am a security professional with some analytical training (both quantitative and qualitative) As I learned to apply these techniques during my doctoral studies, I came to realize the value that they could bring to measuring and analyzing IT security programs Inferential analysis is already used in a variety of industries for process and quality control, and there are definite applications for these techniques in IT security Some techniques are more applicable than others to security challenges in general, and to your security challenges in particular As I describe these statistics, I will take a more general approach, since it is difficult to apply specifics to each of these techniques without describing an entire security metrics project I will reserve detailed explanations of these techniques until the chapter examples

CHAPTER 7:

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