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When you have power and ground, you can start hooking up components between the two to do things. Simple components like resistors and capacitors are considered passive since they do not require a source of energy to perform their task. Passive components usually have two leads (also known as pins or terminals). They are the simplest parts physically but often have the most interesting symbols. In contrast, active components like integrated circuits (ICs) require power and have complex internal functionality, but are represented by simple rectangles bristling with short lines indicating their connection pins.

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should accurately represent the underlying clusters, but not necessarily in proportion to their size in the larger population In the absence of this consideration, it is likely that small population segments may not be detected in a cluster analysis Oversampling these small populations would likely serve to enhance their recovery in the cluster analysis Furthermore, some clustering methods have some bias to nd clusters of relatively equal size, and this tendency can be used to good advantage Of course, random sampling would be desirable if it is essential for the researcher to be able to generalize the results of the study to a target population However, doing so would imply a more theoretically driven analysis as opposed to a more exploratory study Random or strati ed sampling would be useful in replication studies or in more advanced studies attempting to validate a contextual theory.

business and industry executives (Auerbach, 2001; Hays & Brown, 2004; P. Williams & David, 2002). In fact, executive coaching is now a $630 million per year industry with 10,000 coaches located worldwide (Auerbach, 2001). Clinical psychologists, as well as other professionals from a variety of disciplines such as social work, marriage and family therapy, human resources, and so forth, have developed services for leading executives as an executive coach. They generally focus on ways to help executives become better leaders and managers as well as develop strategies to improve interpersonal relationships, productivity, and efficiency in companies. Executive coaches may consult with business leaders about stress management, goal setting, and a host of other topics and services related to human behavior and business. Executive coaching has become a potentially new and lucrative area of work for many clinical psychologists looking to expand their range of professional activities and services (Hays & Brown, 2004).

The selection of the sample elements should consider the overall size of the database A second sample or a split-half sample would be helpful for validation purposes, as discussed later in this chapter As suggested by Milligan (1996), one possible approach is to place arti cially generated idealtype individuals or subjects in the data set The researcher speci es the values for each variable of an ideal-type individual The ideal type would represent a subject or other experimental object that would represent the norm for each group or cluster suspected to be present in the data One or possibly more ideal types would be speci ed for each hypothesized cluster The presence of the correct ideal type or types in a cluster would support the researcher s conceptualization for the hypothesized clustering.

On the other hand, if markedly different ideal types appear in the same cluster, then the researcher s theory or the cluster analysis is suspect The presence of clusters without ideal types may represent groups not yet de ned by the researcher s theory, or possibly subgroups of a larger cluster The user should be warned that the use of ideal types is a temporary process The presence of ideal types in the nal clustering may change the assignment of other elements in the data set The relative in uence of individual data elements has been explored by Cheng and Milligan (1995a, 1995b, 1996a, 1996b) Related to the issue of in uential data points is the issue of outliers Outliers in a clustering context deserve special consideration.

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As stated previously, an outlier in a clustering context refers to an entity that does not fall within the general region of any cluster Note that outliers may or may not have in uence on the clustering solution obtained, and some data points near or in a cluster may have an in uential effect on the clustering process An early simulation study on the effect of outliers in clustering was conducted by Milligan (1980) This research.