### Table 1: Existing and likely uncertainty visualization techniques.

1997

"... In PAGE 6: ...Table 1: Existing and likely uncertainty visualization techniques. Table1 uses twocharacteristics (value and visualization extent) to classify existing uncer- tainty visualization methods. The other characteristics explain and demarcate the space in which visualization methods can be classi ed.... In PAGE 6: ... The listing of all of the characteristics is the complete classi cation, and must be used to quantify a given uncertainty visualization technique. Table1 apos;s upper left cell, contains the most thoroughly researched statistical visualization work: the visualization of a scalar value and its uncertainty,such as the median, quartiles, and outliers of a statistically evaluated variable. If visualized with a discrete visualization extent, the variety of statistical plotting tools is impressive, including glyphs, with various attributes set to denote values, where attributes are the shape, color, etc.... In PAGE 7: ... The taxonomy of existing methods of displaying uncertainty are summarized in Table 2. Our classi cation of uncertainty visualization techniques demonstrates that only the scalar value dis- crete visualization extent, or upper left entry in Table1 has been adequately explored, where... In PAGE 8: ... Entries in Table 3 indicate methods that can be used for an application. The presentation belowis organized by general approach, with detailed description of how a particular method and its relationship to our classi cation scheme in Table1 . But rst, we describe the four di erent applications that wehaveinvestigated, focusing on their relevance to uncertainty visualization and the type of uncertaintyineach case.... In PAGE 19: ...8 Summary Wehaveintroduced a number of new methods for uncertainty visualization as presented in Table 4. These methods are grouped using the characteristics from Table1 , and presented in Table 5. From here, we can see that there is demand for researchintechniques for vector and tensor visualization, and that wehave added techniques for discrete and continuous visualization extents.... ..."

Cited by 36

### Table 1: Existing and likely uncertainty visualization techniques.

1997

"... In PAGE 6: ...Table 1: Existing and likely uncertainty visualization techniques. Table1 uses two characteristics (value and visualization extent) to classify existing uncer- tainty visualization methods. The other characteristics explain and demarcate the space in which visualization methods can be classi ed.... In PAGE 6: ... The listing of all of the characteristics is the complete classi cation, and must be used to quantify a given uncertainty visualization technique. Table1 apos;s upper left cell, contains the most thoroughly researched statistical visualization work: the visualization of a scalar value and its uncertainty, such as the median, quartiles, and outliers of a statistically evaluated variable. If visualized with a discrete visualization extent, the variety of statistical plotting tools is impressive, including glyphs, with various attributes set to denote values, where attributes are the shape, color, etc.... In PAGE 7: ... The taxonomy of existing methods of displaying uncertainty are summarized in Table 2. Our classi cation of uncertainty visualization techniques demonstrates that only the scalar value dis- crete visualization extent, or upper left entry in Table1 has been adequately explored, where... In PAGE 19: ...8 Summary We have introduced a number of new methods for uncertainty visualization as presented in Table 4. These methods are grouped using the characteristics from Table1 , and presented in Table 5. From here, we can see that there is demand for research in techniques for vector and tensor visualization, and that we have added techniques for discrete and continuous visualization extents.... ..."

Cited by 36

### Table 3.2. Standardized canonical coefficients for environmental variables at two scales (Walsh et al. 2001)

in Published

### Table 2: Taxonomy of some existing uncertainty visualization methods as used in di erent appli-

1997

"... In PAGE 7: ... Likewise, adding more variables into existing ow visu- alization methods such as streamlines result in streamballs [BHR + 94], and to hyperstreamlines [DH93]aswell. The taxonomy of existing methods of displaying uncertainty are summarized in Table2 . Our classi cation of uncertainty visualization techniques demonstrates that only the scalar value dis- crete visualization extent, or upper left entry in Table 1 has been adequately explored, where... ..."

Cited by 36

### Table 2: Taxonomy of some existing uncertainty visualization methods as used in di erent appli- cations

1997

"... In PAGE 7: ... Likewise, adding more variables into existing ow visu- alization methods such as streamlines result in streamballs [BHR+94], and to hyperstreamlines [DH93] as well. The taxonomy of existing methods of displaying uncertainty are summarized in Table2 . Our classi cation of uncertainty visualization techniques demonstrates that only the scalar value dis- crete visualization extent, or upper left entry in Table 1 has been adequately explored, where... ..."

Cited by 36

### Table 4: Association of risk variables with total mortality in a multivariate analysis

### Table 6. Results of the uncertainty analysis for the soil exposure pathways

"... In PAGE 17: ... 4.2 SOIL PATHWAYS Table6 presents a descriptive statistical analysis of the Monte Carlo simulations of the risk predictions associated with the uncertainties in the input parameters for the soil exposure models. The point estimate of the risk calculations and the ratios between the point estimates and the 95th and 97.... ..."

### Table 2 Sample uncertainty analysis for F-16XL all values of

"... In PAGE 6: ... Uncertainties with respect to the angle of attack were computed and propagated through the code, proportional to variable gradients with respect to the uncertain variable, via Equation 1. The results from this study are shown as the error bars in Figures 3 and 4 and in Table2 . Figure 3 shows the computed lift coefficient data of Figure 2, with added error bars showing the uncertainty in CL due to a one-sigma uncertainty (for illustration purposes) in the angle of attack (AOA) for an assumed uncertainty in the measured angle of attack given by AOA 0.... In PAGE 7: ...7 variable. Table2 illustrates a typical preliminary uncertainty analysis for the F-16XL configuration. The uncertainties in L C , L dC d , and L dC dq (with in degrees and q in degrees per second) are presented as calculated from first and second derivatives of L C with respect to and q , assuming input 0.... ..."

### Table 15. Hypothetical Spearman correlation uncertainty analysis results.

2007

"... In PAGE 7: ...able 14. Hypothetical stepwise regression and percentile scaling sensitivity analysis results. ...............81 Table15 .... In PAGE 87: ...This information is distributed solely for the purpose of pre-dissemination peer review under applicable information quality guidelines. Sensitivity Analysis on Results from a Two-Stage Monte Carlo Model Run The Pearson correlation, Spearman correlation, and stepwise regression methods of sensitivity analysis discussed in the Sensitivity Analyses section above may also be applied to the results from a two- stage SHEDS run (see Table15 and Table 16). For this purpose, the mean value for each input variable and the mean output statistic are recorded for each of the (MxN) persons in the uncertainty run.... ..."