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Normally, Excel uses what s known as A1 notation. Each cell address consists of a column letter and a row number. However, Excel also supports R1C1 notation. In this system, cell A1 is referred to as cell R1C1, cell A2 as R2C1, and so on. To change to R1C1 notation, select Tools Options, click the General tab, and place a check mark next to R1C1 reference style. After you do so, you ll notice that the column letters all change to numbers. All the cell and range references in your formulas are also adjusted. Table 3-1 presents some examples of formulas using standard notation and R1C1 notation. The formula is assumed to be in cell B1 (also known as R1C2).

If you define both rows and columns, you end up with a grid-like framed document. Figure 22-4 is one example of a framed document with both rows and columns.

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programs targeted toward suspected high risk groups of IDUs, adolescents, and gay men; and (c) intensive risk reduction counseling through traditional clinical and educational channels. Beginning in 1987, this strategy has been subject to a continuous process of both qualitative and quantitative evaluation (Dubois-Arber et al., 1999). For example, Dubois-Arber et al. (1997) reported that, although there had been no changes in level of sexual activity, condom use with a new steady partner increased between 1988 and 1994 from 40% to 64% among 17- to 30-year-olds, and from 57% to 72% among those aged 31 to 45. Systematic condom use with casual partners increased from 8% to 56% between 1987 and 1994 among 17- to 30-year-olds, and from 22% to 42% between 1989 and 1994 among those aged 31 to 45. As one would hope, condom use was higher among those with multiple partners. Based on these ongoing evaluations, recommendations have been formulated by investigators, and used by policymakers. Dubois-Arber et al. (1999) note that the cost of such evaluation is low relative to the amount of information provided, and that this project has also contributed to the development of a culture of evaluation in Switzerland. Upstream approaches have much to recommend them, and often involve integration of downstream and midstream approaches. Thus, far, they have been most successful in smaller countries.

The diagram in Figure 6.22 shows the logic flow that was used for both the encoding and decoding of this technique.

who did not watch television studied frequently, a perfect 1.00 correlation coefficient would likely surface from the statistical equation that calculates the coefficient. Scores close to +1.00 reflect a nearly perfect positive correlation; as scores on one variable increases, so do the scores on the other. Furthermore, a positive correlation also occurs when scores on both variables of interest are low. For example, if scores on depression and scores on hopelessness are assessed in a large group of people, they are likely to be positively correlated. Thus, those who tend to score high on depression are also likely to score high on hopelessness, while those who score low on depression are also likely to score low on hopelessness. When there is no correlation between two variables (e.g., shoe size and intelligence), the correlation is close to .00. It is important to emphasize that the association between two or more variables does not mean that one necessarily caused the other. Correlation does not imply causality. Thus, television viewing does not necessarily cause inadequate studying, and depression does not necessarily cause hopelessness. Additional variables not assessed in a given experiment or study may operate to influence the correlation coefficient. For example, perhaps unmotivated students watch a great deal of television and spend very little time studying. Perhaps these students would spend very little time studying no matter how much television they watched. Other factors (e.g., interest in the subject matter) may also play a role.

The Public Regulated Service (PRS). This provides positioning and timing information to users authorized by governments. It requires a high level of performance with both continuity and access control. Two such signals will be delivered. The main potential users are either European structures like the European Police Of ce (Europol), the European anti fraud Of ce (OLAF), and civilian security forces. Member states structures such as national security services, frontier surveillance forces, or criminal repression forces are also involved. The Search And Rescue (SAR) Service. This is Galileo s contribution to the international COSPAS-SARSAT13 system. Galileo is intended to intercept emergency beacon signals and relay them to national rescue centers. These emergency signals could be transmitted from a ship, a plane, or even from individuals. The advantage of using Galileo is clearly its high accuracy, allowing positioning, together with timing information. This allows a real-time alert in all conditions.

The goal of any data distribution is to provide for increased availability, reliability, and improved query access time. On the other hand, as opposed to query access time,

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