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What's New in @RISK 5
All-new @RISK 5 for Excel has been redesigned from the ground up. A revamped interface with total Excel integration means you will never leave your spreadsheet. The new @RISK Library allows you to share specific probability distributions and results with others in your group. You can also remove @RISK functions for non-@RISK users. The new RiskCompound function combines distributions for insurance and other models, and new Six Sigma functions provide in-depth quality analysis. During simulation, new Demo Mode updates graphs and reports in real-time. New, completely customizable graphs, Scatter Plots, Tornado Mapped Value charts, and Box Plots make communication of results to others a breeze. The Industrial edition of @RISK 5 features all-new RISKOptimizer 5 for optimization under uncertainty.

» Complete list of all new features and changes in @RISK 5

Watch Quick Tips on What's New in @RISK 5
Watch Quick Tips on What's New in RISKOptimizer

 

MODEL SHARING
Swap Out Functions


@RISK Library



Saving @RISK Simulations

INTERFACE
Browse with Tab Key


Model Window





Customizing Model Window



Results Summary Window





Drag and Drop Graphs


Simulation Settings Toolbar

 
"Swap out" @RISK functions so that @RISK models may be shared with—and edited by— others without @RISK installed.
The @RISK Library is a SQL database that lets you share specific probability distributions and simulation results with other @RISK users—all from the standard @RISK modeling interface.
Save @RISK simulation results and graphs directly in your Excel workbook.
 
Use the Tab key or mouse to pop up @RISK graphs of distribution functions or simulation results as you browse your spreadsheet.
The @RISK Model window provides a complete table and thumbnail graphs of all input probability distributions, simulation outputs, and correlation matrices described in your model. You can edit distributions, edit correlations, move through input cells, and more.
The @RISK Model window columns can be customized to select which statistics you want to display on the input distributions in your model, and inputs may also be grouped by category.
The @RISK Results Summary window summarizes the results of your model and displays thumbnail graphs and summary statistics for your simulated output cell and input distributions. You can customize columns to select which statistics you want to display.
Any small thumbnail graph can be expanded to a full window by dragging it off of its summary window onto some blank space.
A new Simulation Settings toolbar provides quick access to the most common simulation settings.
NEW COMMANDS
@RISK Application Settings



BUILDING YOUR MODEL
RiskCompound Function



Overlay Fitted Distributions

Correlations Slider


Correlated Time Series

RiskMakeInput Function








Six Sigma Functions
  » Models
  » Case Studies




 
The Application Settings dialog contains customizable defaults such as graph settings, window configurations, simulations settings, and more.
 
The RiskCompound function combines a frequency and severity distribution in a single function, speeding the modeling of problems in insurance and finance.
Graphs of multiple fitted distributions can be overlaid.
You can dynamically update Scatter Plots of correlated distributions using a new slider bar in the Define Correlations window.
Correlate a time series that has a similar set of distributions in each time period.
The RiskMakeInput function turns any Excel formula into a @RISK simulation input, even if it does not contain a probability distribution. Use this to get @RISK to treat your proprietary calculations just as it does its own probability distributions when calculating simulation results.  RiskMakeInput can also summarize many individual probability distributions into a single input, simplifying your Tornado graphs.
A new RiskSixSigma property function for simulation outputs specifies LSL, USL and Target values for use in Six Sigma statistics calculations. There is also a new set of @RISK statistics functions that return desired Six Sigma statistics on a simulation outputs.
RUNNING SIMULATIONS
Demo Mode



SIMULATION GRAPHS
Overlay Results Graphs



Graph Markers

Graph Titles

Customizing Graphs




Scatter Plots


Scatter from Tornado

Sensitivity Scatter Matrix



Tornado Mapped Values
 
 

 
 
Summary Box Plots


SIMULATION RESULTS
Step Through Simulation

Simulated Correlations

Improved Sensitivity Analysis


 
Put @RISK into Demo Mode to demonstrate to others how Monte Carlo simulation works. During a simulation in Demo Mode, all graphs and statistics are updated every iteration.
 
Easily overlay two or more simulation graphs directly from any graph window. You can also drag graph thumbnails from the Results Summary window onto a graph.
Add markers to your graphs to highlight
important values.
The titles of @RISK graphs can be edited by simply clicking on them.
@RISK uses a new graphing engine specifically for simulation data. Graphs can be fully customized by simply clicking on the desired graph element. Graphs can be copied and pasted in Excel, Word, or PowerPoint.
New Scatter Plots show the relationship
between a simulated output and the samples
from an input distribution.
You can quickly generate a Scatter Plot by dragging a bar of a Tornado graph onto some blank space.
During sensitivity analysis, @RISK can display
of Scatter Plot matrix showing individual Scatter
Plots for each input listed versus each output in
the report.
New Tornado Regression - Mapped Values
graphs show exactly how much a change in an
input affects your bottom line - no math required.
The values on the X-axis show the amount of
change in the output due to a +1 standard
deviation change in each input.
New summary Box Plots quickly show the
mean and percentile values of simulated
outputs in a range.
 
You can step through iterations of a simulation you have run, updating Excel with the sampled values.
Click on a correlation matrix after a simulation to see the simulated correlation coefficients.
@RISK Sensitivity Analysis is improved by pre-screening inputs based on their precedence in formulas to outputs inyour model.

 

 

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