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Tip Dreamweaver saves preview files with a filename like the following: TMP5c34jymi4q.asp; a unique name is generated with each preview to ensure that the browser does not load the page from the cache. If Dreamweaver unexpectedly quits, these TMP files are not deleted. Feel free to delete any such TMP files you find in your site; or use them as backups to restore unsaved work should a crash occur.

If you include Flash SWF files in your exported PDF, note that they will likely not play if they include interactive features such as JavaScripts, buttons, and page actions.



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private function sendData():void { contactService.send({firstname: Joe , lastname: Smith }); }

Dragging a marquee around paths with the Group Selection tool works only for the first series of clicks; dragging another marquee, even over the already-selected paths, just reselects those paths.

3. When the Lens Flare dialog box opens, hold down Alt (Windows), Opt (Mac OS) and click anywhere in the Lens Flare proxy window to access the Precise Flare Center dialog box (Figure 18-2). 4. Enter the X and Y coordinates that you noted earlier. 5. Click the OK button to exit the Precise Flare Center dialog box. 6. Click the OK button in the Lens Flare dialog box. After you exit the Lens Flare dialog box, you will see the lens flare placed precisely where you specified.





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difference is 1.2%, resulting in a z-score of 0.72 (the z-score is 1.2%/1.7%). Such a small z-score is well within a reasonable range, so the difference is not significant. Another way of looking at this is using the 95% confidence interval. The lower bound is at the observed difference minus 1.96*1.7% and the upper bound is the observed difference plus 1.96*1.7%, which comes to a range from 2.2% to 4.6%. Because the confidence interval is both positive and negative, it includes zero. That is, Gotham and Metropolis could actually have the same stop rate, or Metropolis s stop rate could even be bigger than Gotham s (the opposite of the observed ordering). The observed difference could easily be due to randomness of the underlying stop process. This example shows the different ways that the standard error can be used. When confidence intervals do not overlap, the observed values are statistically different. It is also possible to measure the confidence of the difference between two values, using the standard error of the difference of proportions. This calculation uses similar methods. When the resulting confidence interval contains zero, the difference is not significant. The techniques are only measuring a certain type of significance, related to the randomness of underlying processes. The observed values can still provide guidance. There is some evidence that Gotham has a higher stop rate than Metropolis, some evidence but not enough to be confident in the fact. If we had to choose one market or the other for a retention program to save customers, Gotham would be the likely candidate, because its stop rate is larger. However, the choice of Gotham over Metropolis is based on weak evidence, because the difference is not statistically significant.

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As in many other examples, the application relies on two distinct components: the front-end interface and the backend database connection and XML generator. Although there is some additional intelligence in this solution, the bulk of the code is still relying on the basic process of adding data to the database and requesting XML versions of the information already stored. What is important is just how complex an application you can produce using that basic process. The techniques shown in this chapter can be adapted for a wide range of different uses. For example, the application could be adapted to work as a method for directing clients and customers to your home or office from key intersections. The application could also be used as a method to promote different walking routes in your city or town, highlighting different areas. With a small amount of expansion (by adding key points to the database as well as the route points that make up the route sequence), you could turn the system into a way of highlighting important landmarks on an unguided tour of a city. The current application also stores only a basic amount of information about each route. It would be a fairly trivial process to add other features, such as photos, additional markers, or other information. All of the functionality and potential has been demonstrated in this chapter and in earlier chapters about how to add this information.

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