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can be used to check for multicolinearity Correlations between continuous variables, as well as categorical variables, should be checked An example of a multicolinearity situation involving continuous variables is a dataset used to predict a health condition This data set may contain two or more tests that, in fact, measure the same phenomena, and hence only one should be included A multicolinearity situation involving categorical variables involves a model used to predict the success of a marketing campaign In this example, the independent variable color can take three values: red, green and blue To use this variable within the model, the color variable is transformed into three dummy variables corresponding to each color, as discussed in 1 This results in the generation of three new variables; however, an observation where blue is 1 always occurs when red and green are 0.



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10 4

Figure 6.17 Addition of angular momenta in a deformed odd A nucleus. V is the projection of the total angular momentum of the odd nucleon. It is added vectorially to the rotational angular momentum of the core, R, to give the total angular momentum J whose projection on the symmetry axis is K.





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Hence, only two variables are really needed to capture all possible scenarios The inclusion of all three variables would include correlations between the color variables and therefore all three should not be used After a model is built, multicolinearity may be observed through interpreting the beta coef cients to look for, as an example, unexpected positive or negative numbers that do not re ect how the model is expected to behave The following sections discuss how a multiple linear regression model is built, and, once built, how its assumptions are tested through an analysis of the errors Most statistical software packages generate a series of statistics concerning the models built, such as the standard error and the coef cient of multiple determination, along with metrics to assess the signi cance of the models and the parameters.

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Source: Radioisotope Tracers in Industry and Geophysics. Vienna: International Atomic Energy Agency, 1967.

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Windows help files can be used with message boxes. To do this, you need to specify the name of the help file to use as an additional parameter. Following the help file name, you can add a context identifier, which is a numerical value that points to a specific location in the help file. To specify a help file and context identifier, use the following syntax:

Finally, in building a model, alternative combinations of variables should be used to build multiple models, and alternative data transformations (such as product of variables or variables squared) can be considered to improve the quality of the models built..

LISTING 28-1

In practice, this is done by the sender dividing the transmission into blocks which are sent one by one. The receiver conflrms that it has understood each block and the next block can then be sent.

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The Ih symmetry of the 60-atoms molecule allows 2As and 8 H , modes to be Raman active and 4T1, modes to be IR active. The four IR active modes are at 1430, 1185, 580 and 528 cm-', respectively. The most important Raman modes are at 1469 (tangential bond alternation or pinch mode, As), 495 (radial breathing mode, A s ) and 271 (squashing mode, Hh')cm I , respectively. In the low temperatur phase degenerate modes split from a crystal field and Davidov interaction. Good reviews on the group theoretical analysis and on the line positions are given in (Dresselhaus et al., 1992; Matus and Kuzmany, 1993).

10 6 10 5 0 5 10 15 Normalized Average SNR of First Path [dB]

That bad news on the inflation front as the new decade began postponed any additional monetary easing by the U.S. Federal Reserve Board, at least for the time being. In mid-January of 1990, Fed Vice Chairman Manuel Johnson and Fed Governor Wayne Angell, both of whom were mentioned in the previous chapter, stated that any further Fed easing would be put on hold. Wayne Angell specifically mentioned the need for commodity prices to start dropping as a requirement for further Fed easing. Advances in key commodity markets had heightened fears of a global shift to higher inflation and were clearly influencing monetary decisions made by central bankers around the world, including our own Federal Reserve Board. Figures 8 23 and 8.24 show the upward pressure on global interest rates as the new decade began. Figure 8.25 reveals a strong visual correlation between global equity markets, many of which were setting new highs as 1989 ended. SUMMARY This chapter extended our intermarket analysis to the international realm. It showed that trends in commodity prices (inflation), interest rates, and stocks are visible on

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