 Part 1. Introduction to MM4XL
 Part 2. MM4XL Tools
 1. Strategic Tools
 BCG Matrix
 Brand Mapping
 Brand Switch
 Decision Tree
 Forecast Manager
 McKinsey Matrix
 Profile Manager
 Quality Manager
 Risk Analyst
 Risk Analyst Expert in a Few Minutes
 Introduction to Decision Analysis
 Introducing Risk Analyst with an example
 1. How to run Risk Analyst
 2. Simulation Never heard of it
 3. Examples
 4. Functions
 1. Property Functions
 2. Utility Functions
 3. Distribution Functions
 mmBETA (Scale, Shape)
 mmBETAGEN (Scale, Shape, [Optional: Lower], [Optional: Upper])
 mmBINOMIAL (Trials, Successes)
 mmCHI2 (Degrees)
 mmDISCRETE (InputRange, Probabilities)
 mmERF (Mean)
 mmERLANG (Scale, Shape)
 mmEXPON (Mean)
 mmEXTVAL (ModalValue, StDeviation)
 mmGAMMA (Scale, Shape)
 mmGAUSSINV (Mean, Scale)
 mmGEO (Trials)
 mmHYPERGEO (Sample, Defects, BatchSize)
 mmINTUNI (Lower, Upper)
 mmLOGISTIC (Mean, StDeviation)
 mmLOGNORMAL (Mean, StDeviation)
 mmNEGBIN (Failures, Successes)
 mmNORMAL (Mean, StDeviation)
 mmPARETO (Location, ModalValue)
 mmPARETO2 (Location, ModalValue)
 mmPERT (Lower, ModalValue, Upper)
 mmPOISSON (Mean)
 mmRANDBETWEEN (Lower, Upper)
 mmRAYLEIGH (ModalValue)
 mmSTUDENT (Degrees)
 mmTRI (Lower, ModalValue, Upper)
 mmUNIFORM (Lower, Upper)
 mmWEIBULL (Life, Shape)
 Probability functions
 Technicalities
 Sources
 2. Analytical Tools
 Business Formulas
 mmBASS, Bass Diffusion Model
 mmBEI, Brand Equity Index
 mmBEP, BreakEven Point
 mmBEPR, BreakEven Point with Fixed Rate of Return
 mmBUYRATE, Purchase Rate Model
 mmCAGR, Compound Annual Growth
 mmCHIp, Chi Squared Test
 mmCODING, Coding of variables
 1. Customer Satisfaction
 2. Database Functions
 mmDHMS, Number to Time
 mmEI, Evolution Index
 mmEXPECT, Expected values
 3. Forecast Errors
 mmGROWTH
 mmGROWTHBACK
 mmGRP, Gross Rating Points
 mmHERF, Herfindahl Index
 mmINTERPOLE, Linear Interpolation
 mmLEARN, Learning Curve
 mmMSAR, Market Share to Advertising Ratio
 4. Opportunity Index
 5. Performance Ranking
 6. Project Management
 mmPREMIUM, Price Premium
 mmPRESS, Product Performance Index
 7. Price Indexes
 8. Queuing Theory
 mmRANGE
 mmREBUY, Repeat Purchase Rate
 mmREBUYS, Estimated Number of RePurchases
 mmRELATIVE
 mmSAMPLE, Sample Size
 mmSAMPLEMIN, Minimum Sample for Significant Values
 mmSEASON, Seasonality Indexes
 mmSHARE
 mmSIGNIF, Significance Test
 mmVARc, Coefficient of Variation
 Cluster Analysis
 CrossTab
 Descriptive Analyst
 Gravitation Analysis
 Proportion Analyst
 Sample Manager
 Segmentation Tree
 Variation Analyst
 3. Charts and Maps
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 Part 1. Introduction to MM4XL
 Part 2. MM4XL Tools
 1. Strategic Tools
 BCG Matrix
 Brand Mapping
 Brand Switch
 Decision Tree
 Forecast Manager
 McKinsey Matrix
 Profile Manager
 Quality Manager
 Risk Analyst
 1. How to run Risk Analyst
 2. Simulation Never heard of it
 3. Examples
 4. Functions
 1. Property Functions
 2. Utility Functions
 3. Distribution Functions
 mmBETA (Scale, Shape)
 mmBETAGEN (Scale, Shape, [Optional: Lower], [Optional: Upper])
 mmBINOMIAL (Trials, Successes)
 mmCHI2 (Degrees)
 mmDISCRETE (InputRange, Probabilities)
 mmERF (Mean)
 mmERLANG (Scale, Shape)
 mmEXPON (Mean)
 mmEXTVAL (ModalValue, StDeviation)
 mmGAMMA (Scale, Shape)
 mmGAUSSINV (Mean, Scale)
 mmGEO (Trials)
 mmHYPERGEO (Sample, Defects, BatchSize)
 mmINTUNI (Lower, Upper)
 mmLOGISTIC (Mean, StDeviation)
 mmLOGNORMAL (Mean, StDeviation)
 mmNEGBIN (Failures, Successes)
 mmNORMAL (Mean, StDeviation)
 mmPARETO (Location, ModalValue)
 mmPARETO2 (Location, ModalValue)
 mmPERT (Lower, ModalValue, Upper)
 mmPOISSON (Mean)
 mmRANDBETWEEN (Lower, Upper)
 mmRAYLEIGH (ModalValue)
 mmSTUDENT (Degrees)
 mmTRI (Lower, ModalValue, Upper)
 mmUNIFORM (Lower, Upper)
 mmWEIBULL (Life, Shape)
 Probability functions
 Risk Analyst Expert in a Few Minutes
 Introduction to Decision Analysis
 Introducing Risk Analyst with an example
 Technicalities
 Sources
 2. Analytical Tools
 Business Formulas
 1. Customer Satisfaction
 2. Database Functions
 3. Forecast Errors
 4. Opportunity Index
 5. Performance Ranking
 6. Project Management
 7. Price Indexes
 8. Queuing Theory
 mmBASS, Bass Diffusion Model
 mmBEI, Brand Equity Index
 mmBEP, BreakEven Point
 mmBEPR, BreakEven Point with Fixed Rate of Return
 mmBUYRATE, Purchase Rate Model
 mmCAGR, Compound Annual Growth
 mmCHIp, Chi Squared Test
 mmCODING, Coding of variables
 mmDHMS, Number to Time
 mmEI, Evolution Index
 mmEXPECT, Expected values
 mmGROWTH
 mmGROWTHBACK
 mmGRP, Gross Rating Points
 mmHERF, Herfindahl Index
 mmINTERPOLE, Linear Interpolation
 mmLEARN, Learning Curve
 mmMSAR, Market Share to Advertising Ratio
 mmPREMIUM, Price Premium
 mmPRESS, Product Performance Index
 mmRANGE
 mmREBUY, Repeat Purchase Rate
 mmREBUYS, Estimated Number of RePurchases
 mmRELATIVE
 mmSAMPLE, Sample Size
 mmSAMPLEMIN, Minimum Sample for Significant Values
 mmSEASON, Seasonality Indexes
 mmSHARE
 mmSIGNIF, Significance Test
 mmVARc, Coefficient of Variation
 Cluster Analysis
 CrossTab
 Descriptive Analyst
 Gravitation Analysis
 Proportion Analyst
 Sample Manager
 Segmentation Tree
 Variation Analyst
 3. Charts and Maps
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Part 2. MM4XL Tools > 1. Strategic Tools > Risk Analyst > 1. How to run Risk Analyst > 2. Model Report > Simulation report
Risk Analyst Simulation report When the checkboxes Simulations of outputs and Simulations of inputs are active in page Report of the Simulation Settings window Risk Analyst prints all simulated values for all reported variables. Row 13 to 16 of the simulation report show identifiers for the variables accounted in the model (more precisely, for all variables not locked with the mmLOCK function). In row 13 there is the Variable type. Models in Risk Analyst use two kinds of variables: Output and Input. Formula and Cell address show what they promise, and in row Name there is shown the name, if any, that the modeler entered in the function mmNAME for the variable. Examples of simulation reports can be found in the example files accompanying the Risk Analyst tool of MM4XL software. From row 18 on are shown the single simulated values for all unlocked variables. In column A there are progressive numbers and from column B on there are the simulated values. These values may be useful to inspect the shape of the distribution modeled by any one function. It is, however, not very frequent to go down in such analytical detail when inspecting a model, unless you have a good reason to do it. Other reports may help better getting an understanding of the simulated values. If you really have or want to, consider using the function mmHISTO to group simulated variables in intervals as shown in histogram charts. Statistics When the checkbox Detailed statistics is active in page Report of the Simulation Settings window Risk Analyst prints, for all reported variables, a number of descriptive statistics and percentile values In row 916 there are 8 descriptive statistics for each variable. The same values can be produced with Descriptive Analyst, one of tools of MM4XL software, which can also print a box plot that shows in a very intuitive manner the characteristics of the shape of a variable. In row 1836 there are percentile values that show limits at fixed interval of 5%. For instance, a percentile value equal to 0.125 for 10% means that all random values for the variable with a value of 0.125 or less are 10% of all sampled values. If these are 1000 trials, 100 would be equal or smaller to 0.125. Percentile values are also used to draw the Time Series report. They can be computed with the Excel formula: =PERCENTILE(InputRange, %Level) Sensitivity When the checkboxes Sensitivities and Tornado charts are active in page Report of the Simulation Settings window Risk Analyst prints a table of values and a bar chart for each output variable. The analysis shows the correlation values of one output variable with each input variable in the model. Correlation values help identifying the impact of each input variable on the output variable(s). The following chart shows the correlation values of four input variables (bars in the following chart) and an output variable called Gross Profit. It is clear that the variable in cell C19 is exerting a strong influence in orientating the results of the output variable, while all other inputs have only a marginal impact. If we are in need to change the model in order to produce a different outcome, variable C19 is the best candidate to start having a look to. Input charts When the checkbox Input charts is active in page Report of the Simulation Settings window Risk Analyst prints, for each input variable in the model, a table of values and a histogram chart. The chart below is from an input variable that refers to 1000 runs drawn with mmBINOMIAL(100,0.25). The chart shows the shape of the distribution, That should be coherent with the simulationist?s assumption, the frequency and relative frequency for each class. The smallest bar on the left, for instance, refers to 8 simulated values with value 14.727 and lower; in class 2, 39 values reported a value above 14.727 but equal or smaller than 17.455 and so on. The same chart can be produced using the simulated values of any variable either with the function mmHISTO or using the MM4XL tool called Descriptive Analyst. The latter tool can also draw box plots, which are very useful charts to describe the shape of a distribution. Output charts When the checkbox Output charts is active in page Report of the Simulation Settings window Risk Analyst prints, for each output variable in the model, a table of values and a histogram chart, exactly as described in the section Input charts of this Help chapter. 