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Figure 6.33 S-parameter S22 comparison as a function of frequency for a SiGeC HBT device before and after ESD HBM stress

Before discussing continuous probability distributions, such as the normal, we need to introduce additional terminology.

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I often work with companies that wish to protect their intellectual property. In one particular case it turned out that a competitor was releasing similar products and beating them to market. After this happened several times the management finally realized that something was seriously wrong. In looking at this company s situation I noted that it was part of its corporate culture that encryption was not used on any of the servers or for any communication. I was able to use that information to find the person who was committing corporate espionage. I knew that there were no supported company-wide encryption programs and no policies stating that encryption be used. That suggested to me that there should not be any encrypted traffic on the network. Therefore, I set up a system that would pull data off the network and run it through a program that could detect whether data had been encrypted. I began to see a pattern: Two accounts were being used to send large amounts of encrypted data to anonymous email addresses. This became even more suspicious when I realized that both accounts belonged to the same person. I was able to use the fact that encryption had been detected to focus in on this individual and help the company take legal action, even though I had no idea what the encrypted material said.

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where x+1 represents the odds ratio for those who are a unit apart on X , controlling for all other covariates in the model. Equation 20.9 shows that the odds of the event for those with an X value of x + 1 is higher by a factor of e 1 than for those with an X value of x. In logistic regression, the odds ratio is the multiplicative analogue of the unstandardized coef cient in linear regression. Like the latter, it indicates a constant change in the response for a unit increase in a given predictor, except in this case it is the multiplicative, rather than additive, change in the odds. Because the odds ratio is such a staple of interpretation in logistic regression, it is worth exploring further. Consider the zero-order impact of substance abuse on violence: Of the 4,151 couples with no substance abuse, 509 reported violence. For this group, then, the probability of violence is 509/4151 = .123, and the odds of violence is therefore .123/(1 .123) = .140. Among the 250 couples with substance abuse problems, 77 reported violence. Their probability of violence is therefore 77/250 = .308, implying an odds of violence of .308/(1 .308) = .445. To quantify the effect of substance abuse on violence, we take the ratio of the odds, or .445/.140 = 3.179. That is, substance abuse raises the odds of violence by a factor of 3.179. Or, the odds of violence is 3.179 times higher for those with substance abuse problems. Notice that it is incorrect to say that those

concern about global environmental issues (Uzzell, 2000b) Exposure to constraints creates a disequilibrium, and the individual, having a tendency to reincorporate initial behavior, reverts to the earlier state of equilibrium Adaptation: The Ability to Put Up With a Constraining Situation in so Far as It Is Continuous Observing behavior in the urban environment provides evidence of the constraining conditions of the urban context Residents of large cities walk faster in the street and demonstrate greater withdrawal than do those living in small towns: They look straight ahead, only rarely maintain eye contact with others, and respond less frequently to the various requests for help from other people In other words, faced with an overstimulating urban environment, people use a ltering process by which they focus their attention on those requests that they evaluate as important, disregarding peripheral stimulation.

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