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The random variable X is defined to be equal to the number of wafers that pass. The last column of the table shows the values of X that are assigned to each outcome in the experiment. EXAMPLE 3-3 Define the random variable X to be the number of contamination particles on a wafer in semiconductor manufacturing. Although wafers possess a number of characteristics, the random variable X summarizes the wafer only in terms of the number of particles. The possible values of X are integers from zero up to some large value that represents the maximum number of particles that can be found on one of the wafers. If this maximum number is very large, we might simply assume that the range of X is the set of integers from zero to infinity. Note that more than one random variable can be defined on a sample space. In Example 3-3, we might define the random variable Y to be the number of chips from a wafer that fail the final test.

We now focus on the imperative portion of the Monitor task. Figure 5.10 shows the code listing for the members of the Monitor class. Lines 1-20 in this case are automatically generated by the software synthesis tool that inspects the declarative part of the ATaG program for this purpose. Lines

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move. Flash Player does execute all 500 iterations of this loop, and each assignment is made in order (x holds the value 0, then 1, then 2, and so on), but nothing makes its way to the screen until all the code is completed. Because Flash Player works this way, you have to be aware of the order that things occur. Although action B might occur far after action A in code, the user cannot see this gap in time represented on the screen. And if you set a variable to something in reaction to an event, there may be frames that execute for which that variable is not yet set. A side effect of the order in which Flash Player operates is that involved computation can slow down or halt the rendering of new frames. This is also the reason that, when an uncaught exception aborts all ActionScript on a frame, the results can be fatal. Skipping to ActionScript executed in the next frame can ignore hundreds or thousands of lines of code. ActionScript that you write isn t concurrent. It can t be threaded or fork off processes. It executes from top to bottom. However, native Flash Player API calls may execute in parallel behind the scenes, like network accesses. You can use some asynchronous events like those broadcast by Timer (see 22, Timers and Timer-Driven Programming ) and the Event.ENTER_FRAME event to schedule ActionScript to execute after one or more frames are rendered. Correspondingly, you can use updateAfterEvent() methods to request a frame to draw immediately after ActionScript processing nishes, regardless of when the next frame is scheduled to render. These asynchronous events are the primary way that ActionScript gets executed in frames after the rst one; as such, they can make things animate.

Table 3-1 Wafer Tests Outcome Wafer 1 Pass Fail Pass Fail Wafer 2 Pass Pass Fail Fail Probability 0.64 0.16 0.16 0.04 x 2 1 1 0

At the core of any programmatic animation is some event that is red at regular intervals. This enables ActionScript to be executed repeatedly across time, rather than all at once. If you can move an object a tiny bit at a time at regular intervals, you have achieved animation. I will show simple examples of building animation from scratch using only Event.ENTER_FRAME or a Timer. Many examples in previous chapters use these simple time-based animations, but in this section you ll learn how to re ne those methods. Creating these examples yourself will give you an understanding of what s happening behind the scenes and enable you to create your own animation code when premade animation packages do not suf ce. This chapter will only get you started with animation principles with ActionScript. For a guide to creating algorithmic motion in code, including basic physics, particles, and forward and inverse kinematics, take a look at Foundation ActionScript 3.0 Animation: Making Things Move! by Keith Peters (Friends of ED, 2007).

appear to be operating in a state of statistical control at the desired target level 16-40. The concentration of a chemical product is measured by taking four samples from each batch of material. The average concentration of these measurements is shown for the last 20 batches in the following table: Batch 1 2 3 4 5 6 7 8 9 10 Concentration 104.5 99.9 106.7 105.2 94.8 94.6 104.4 99.4 100.3 100.3 Batch 11 12 13 14 15 16 17 18 19 20 Concentration 95.4 94.5 104.5 99.7 97.7 97.0 95.8 97.4 99.0 102.6

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