Input Shading, Tornado Overlays and Contribution to Variance tornado graphs have all been added to the already powerful collection of tornado graphs that previous versions of @RISK had to offer. Input Shading (See #1 in image below) We've added a shading option to our Change in Output Mean Tornado graphs to have the ability to quickly see whether the input associated with each bar is high or low when the output statistic increases or decreases. In the example below you can see that when inputs such as Product Lifetime and Initial Unit Price are high, there is a positive impact on the net present value (NPV) of the project; when an input such as Initial Cost is high it will have a negative impact on the NPV.

Contribution to Variance (See #2 in image below) @RISK's new Contribution to Variance tornado graphs help you understand how much of the variance in the output variable is attributable to each individual input. There are options for displaying both the magnitude and direction of the bars, or just the magnitude.

The former displays bars to the left and right of the centerline, depending on the correlation between the input and the output, while the latter displays all input bars to the right (as shown below), so the contribution to variance can be more easily compared. Tornado Overlays (See #3 in image below) You can now overlay multiple tornado graphs to make specific comparisons easy to understand and communicate to others. This is especially helpful when you want to compare pre-mitigation vs post-mitigation on the same model; or if you would simply like to compare the results of multiple simulations to analyze other strategies. Statistics functions return desired statistics on simulation results for 1) a specified cell or 2) a simulation output or input. These functions are updated in real time as a simulation is running or at the end of a simulation. Statistics functions located in template sheets used for creating custom reports are updated only when a simulation is completed. All of the following functions can use the RiskTruncate property function to optionally restrict the range of the simulated distribution for calculating the statistic.

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• RiskCIMean ( cellref or output/input name,confidence level,lower bound,Sim# ) returns the lower or upper bound of the confidence interval of the mean of the simulated distribution for cellref. Instead of a single point estimate for the mean, a confidence interval generates lower and upper bounds for the possible value of the mean, at a given confidence level. • RiskCoeffOfVariation ( cellref or output/input name,Sim# ) returns the coefficient of variation of the simulated distribution for cellref. The coefficient of variation is a measure of dispersion of a probability distribution or frequency distribution. It is often expressed as a percentage, and is defined as the ratio of the standard deviation to the mean. • RiskMeanAbsDev ( cellref or output/input name,Sim# ) returns the mean absolute deviation of the simulated distribution for cellref.

Mean Absolute Deviation is the mean of the data's absolute deviations around the data's mean or the average (absolute) distance from the mean. • RiskSemiStdDev ( cellref or output/input name,lower_data,Sim# ) returns the semi standard deviation of the simulated distribution for cellref, or the standard deviation of the values in the distribution below the mean. • RiskSemiVariance ( cellref or output/input name, lower_data, Sim# ) returns the semi variance of the simulated distribution for cellref, or the variance of the values in the distribution below the mean. • RiskStdErrOfMean ( cellref or output/input name,Sim# ) returns the standard error of the mean of the simulated distribution for cellref. In addition to @RISK's New Features the following Maintenance Fixes have also been taken care of. *** A Selection of Significant Maintenance Fixes *** 12541 “Swap Out” Summary Report sometimes displays incorrect thumbnail graph image. 12475 'Overflow' message when running Stress Analysis with very large number of iterations.