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A chart with two value axes is appropriate because the two data series vary dramatically in scale. If the Sales data was plotted using the left axis, the line would barely be visible. Most charts provide some method of identifying the data series or data points. A legend, for example, is often used to identify the various series in a chart. In this example, the legend appears on the bottom of the chart. Some charts also display data labels to identify speci c data points. This chart displays data labels for the Calls series, but not for the Sales series. In addition, most charts (including the example chart) contain a chart title and additional labels to identify the axes or categories. It also contains horizontal grid lines (which correspond to the left value axis). Grid lines are basically extensions of the value axis scale, which makes it easier for the viewer to determine the magnitude of the data points. All charts have a chart area (the entire background area of the chart) and a plot area. The plot area shows the actual chart, and in this example, the plot area has a different background color. Charts can have additional parts or fewer parts, depending on the chart type. For example, a pie chart has slices and no axes. A three-dimensional (3-D) chart may have walls and a oor. You can also add many other types of items to a chart. For example, you can add a trend line or display error bars. In other words, after you create a chart, you have a great deal of exibility in customizing the chart.



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Studies by Yee (1995) on Southeast Asians in the United States as well as Tran (1993) on Vietnamese con rmed the hypothesis that acculturation stress coupled with stressful experiences lead to poorer health Similarly, Cheung and Spears (1995) assume a strong association between negative life events and depression among Cambodian immigrants in New Zealand Moreover, they identi ed lack of acculturation, feelings of discrimination, and poor language skills as risk factors for mental disorders Chung and Kagawa-Singer (1993) examined predictors of psychological distress among Southeast Asian refugees Even ve years after arrival in the United States, premigration stressors, such as number of years in the refugee camp, number of traumatic events, and loss of family members, signi cantly predicted depression Apart from cultural changes, living conditions for immigrants are often below average, especially for refugees from Third World countries..





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the rst principal component, since it explains nearly half the variability Or should we retain all eight components, since they explain 100% of the variability Well, clearly, retaining all eight components does not help us to reduce the number of distinct explanatory elements As usual, the answer lies somewhere between these two extremes Note from Table 13 that the eigenvalues for several of the components are rather low, explaining less than 2% of the variability in the Z -variables Perhaps these would be the components we should consider not retaining in our analysis The criteria used for deciding how many components to extract are (1) the eigenvalue criterion, (2) the proportion of variance explained criterion, (3) the minimum communality criterion, and (4) the scree plot criterion Eigenvalue Criterion Recall from result 1 that the sum of the eigenvalues represents the number of variables entered into the PCA.

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An eigenvalue of 1 would then mean that the component would explain about one variable s worth of the variability The rationale for using the eigenvalue criterion is that each component should explain at least one variable s worth of the variability, and therefore the eigenvalue criterion states that only components with eigenvalues greater than 1 should be retained Note that if there are fewer than 20 variables, the eigenvalue criterion tends to recommend extracting too few components, while if there are more than 50 variables, this criterion may recommend extracting too many From Table 13 we see that three components have eigenvalues greater than 1 and are therefore retained Component 4 has an eigenvalue of 0.

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Figure 9.2 Evolution scenario of the world energy demand and of CO2 emissions between now and 2050. Reproduced with permission from Energie & Climat: R ussir e la transition nerg tique by Alexandre Rojey, Editions Technip, Paris, 2008 e e

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