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we might observe this difference in the sample errors even when errorv(hl) 5 errorv(h2) What is the probability that errorv(hl) > errorv(h2), given the observed difference in sample errors 2 = 10 in this case Equivalently, what is the probability that d > 0, given that we observed 2 = lo Note the probability Pr(d > 0) is equal to the probability that 2 has not overestimated d by more than lo Put another way, this is the probability that 2 falls into the one-sided interval 2 < d lo Since d is the mean of the distribution 2 lo governing 2, we can equivalently express this one-sided interval as 2 < p To summarize, the probability Pr(d > 0) equals the probability that 2 falls into the one-sided interval 2 < pa + lo Since we already calculated the approximate distribution governing 2 in the previous section, we can determine the probability that 2 falls into this one-sided interval by calculating the probability mass of the 2 distribution within this interval Let us begin this calculation by re-expressing the interval 2 < pi 10 in terms of the number of standard deviations it allows deviating from the mean Using Equation (512) we find that 02 FZ 061, so we can re-express the interval as approximately

Jackson holds a BBA from Westminster College (PA), an MEd from the University of Pittsburgh, and an MA from Teachers College, Columbia University Selected as a participant in the Institute for Educational Management at Harvard University in 1985, he received the Administrative Development Award from Colgate University that year He has served as distinguished instructor of career life planning for the American Management Association s Operation Enterprise Program Jackson has published articles on teaching English as a foreign language and career planning for undergraduates In the fall of 1989, he was one of three Americans selected to participate in an international seminar on career planning and placement at the University of Oxford in England Since 1997, Jackson has taught writing at Terra Community College and Owens Community College in Ohio C Kathleen Geckeis lived in Germany and studied German, art history, and British and American literature at the Universit t des Saarlandes from 1977 to 1986 As methodology instructor at the Berlitz School of Languages in Saarbr cken, Saarland, she taught English as a Foreign Language, as well as Business English to corporations, such as Mannesmag Demag and the Deutsche Bank, from 1980 to 1986 In 1988, Geckeis received a BA in German Language, Literature, and Translation, cum laude At the top of the class, she was first to receive an MA in German Translation and Literature from the Applied Linguistics Institute at Kent State University In 1997, Geckeis earned an MA in English from the University of Toledo A ten-year veteran of community college education, she has taught and developed a variety of courses, including Elementary and Intermediate German, Composition I and II, Technical Report Writing, Business Communication, the American Novel, Short Fiction, Introduction to Humanities, Critical Thinking, Business for International Trade, and Developmental Reading and Writing Geckeis has also worked as a freelance interpreter and as an in-house translator Since 2000, Geckeis has been the Manager of the Writing Center at Owens Community College In the spring of 2002, Geckeis presented a paper at the International Writing Centers Association Conference in Savannah, GA.

Now the code s in place. Start up Interface Builder by double-clicking on the MainView.xib entry in the detail panel (not MainWindow.xib this is just a placeholder NIB file). You will see the Interface Builder user interface more or less as normal (see Figure 4 4).

What is the confidence level associated with this one-sided interval for a Normal distribution Consulting Table 51, we find that 164 standard deviations about the mean corresponds to a two-sided interval with confidence level 90% Therefore, the one-sided interval will have an associated confidence level of 95% Therefore, given the observed 2 = lo, the probability that errorv(h1) > errorv(h2) is approximately 95 In the terminology of the statistics literature, we say that we accept the hypothesis that "errorv(hl) > errorv(h2)" with confidence 095 Alternatively, we may state that we reject the opposite hypothesis (often called the null hypothesis) at a (1 - 095) = 05 level of significance

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