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In Table 7.7, a residual value has been calculated using the actual (y) and the predicted (y) values. It is important to analyze residuals based on a number of factors, including the following: Response variable: There should be no trends in residual values over the range of the response variable, that is, the distribution should be random. Frequency distribution: The frequency distribution of the residual values should follow a normal distribution. Observation order: There should be no discernable trends based on when the observations were measured. Figure 7.8 illustrates an analysis of residuals for a simple model. The model is excellent as indicated by an r 2 value of 0.98. The scatterplot showing the residuals plotted against the response variable shows a reasonably even distribution of the residuals. The frequency distribution of the residual values follows a normal distribution. No trend can be seen in the residual values based on the order of the observations.

How often people lie is a dif cult question to investigate. Probably the most popular method is to ask people to report how many lies they have told during a certain period of time (Cole, 2001; Arnett Jensen, Arnett, Feldman, & Cauffman, 2004; Vrij, Floyd, & Ennis, 2003). The question is how reliable are the outcomes For example, are people really aware of the number of lies they tell And are they willing to admit all their lies they remember, including the serious lies Another method is to ask participants to write down the last lie they told (Backbier & Sieswerda, 1997). Again, there is no guarantee that people will actually remember the last lie they told, particularly if this was a trivial lie. Also, they may not be willing to share their last lie in case it was a serious lie. Yet another method is by showing participants hypothetical scenarios and asking them to indicate whether they would lie is such a scenario (Argo, White, & Dahl, 2006; Williams, 2001). With this method, there is no certainty that participants would actually respond in reality as they indicated they would in the scenario. Alternatively, people are asked to keep a diary of all the social interactions they have and to note how often they lied during these social interactions (DePaulo, Kashy et al. s, 1996, diary study introduced above). Again, people may not be willing to report some of the serious lies they told. Also, instructing participants to report their social interactions may affect the nature

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Allocation Effect: CAM s overweight position in a sector that performed better than the overall index contributed 7 basis points to the outperformance (see Exhibit 9.13). Selection Effect: CAM s stock selection in this sector was better than the index s sector performance and because the sector is a large component of CAM s portfolio, the impact due to selection was fairly sizable, at 35 basis points.

Because fruit contains sugar, it sometimes gets a bad wrap. Perhaps you ve eaten some fruit and found your blood glucose level rose afterward. However, this doesn t mean that fruit is unhealthy. What it does mean is that although you should eat fruit daily, you shouldn t eat it in unrestricted amounts. A medium-sized piece of fruit at each meal is generally sufficient. Also, if eating appropriate quantities of fruit still makes your blood glucose level go up unduly, you should get in touch with your dietitian, to ensure that you re eating the right amount of fruit, and your doctor, to see if your diabetes medications need adjusting.

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If you ask for the size() of the attrs variable, you will always be returned a value of 4. Performance optimizations As with all the enterprise APIs, you can use various performance optimizations to get the most from your system. We have already touched on a number of them in the tips throughout the chapter. Here are a few more to add to the collection. Each time you create a new initial context you are opening another connection to the underlying service. If you are dealing with files, this causes no real performance penalty, but if you are going across an encrypted network link to a server, it can be very costly. Avoid creating new contexts all the time by keeping the basic initial information and then querying for sub contexts from that. Each initial context will keep the connection information. Unfortunately, this also means that JDBC does not provide with an equivalent of explicit connection pooling. You really have to rely on the underlying service provider implementation to deal with any pooling, or write your own system over the top of the basic classes. In most applications, pieces of code usually know when they require only a subset of the data provided by the directory service. If you use the version of getAttributes() that requests this subset, it provides a filtering 182

12: Don t Forget Your Veggies!

Marchetti, C., & Della Salla, S. (1998). Disentangling the alien and anarchic hand. Cognitive Neuropsychiatry, 3, 191 208.

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