# Reviewing the simulation results in Tamara

When
the simulation is complete, *Tamara*
will show a window like this:

On the left of the screen each parent and child task is listed. By default, the Level 0 task (entire project) is selected at the end of the simulation run. You can select any task or sub-task from this list.

In
the middle will appear a plot related to the selected task, and to its
right some basic statistics relating to the plot. At the end of a simulation,
*Tamara* shows a histogram of
the finish date of the entire project by default.

You can change the graph to be displayed by selecting from one of the icons in the View group in the ribbon at the top of the screen:

You can choose to show the start date, finish date, duration or total costs of a task by selecting one of the icons in the Type group in the ribbon:

The start and finish dates take account of any project calendars that were specified in the original Primavera or Project schedule model, and will usually therefore show gaps in the histogram for weekends when the scaling used is days.

The scaling of the horizontal axis can be changed by selecting one of the icons in the Step group in the ribbon:

*Tamara*
offers
ten different plots of the simulation results, described below. They are:

The ribbon controlling how the plot is presented changes depending on the type of plot selected.

## Histogram plot

The ribbon shown with the Histogram plot is as follows:

The histogram plot shows the duration, start date, finish date or cost of the selected task on the horizontal axis and the probability of that duration (or date) occurring on the vertical axis. For example, the following plot shows the duration of the task ‘Detail, fabricate and deliver steel’ project:

The histogram plot is a useful visualization for the range of durations (between 55 and 75) and the most likely (64 days).

The vertical axis is labelled ‘Probability density’, which is the technically correct term to use, because the probability is actually the area under this curve. However, for practical purposes you can just think of it as the probability of the horizontal axis value occurring. The most frequent simulated value is at 64 days, which is the tallest bar towards the middle of the plot. The bar’s height of about 0.1 (or 10%) shows the fraction of the simulation data that rounded to 64 days. We can summarize this as saying ‘There’s a 10% chance the task will take 61 days’. The probabilities (sum of the histogram bar heights) sum to 100%.

**Note**:
one can read from the
plot that *there is a 10% chance
the task will take 64 days*. One should be careful when using such
expressions. People who are somewhat unfamiliar with probability concepts
will often say something like *there
is a 50% chance the project will take 120 days*, when what they
really mean is *there is a
50% chance the project will take less
than 120 days*.

## Cumulative ascending plot

The
cumulative ascending plot (sometimes known as an S-plot) shows the duration
(or date) on the horizontal axis and the probability of *falling
below* that duration (or date) on the vertical axis. For example, the
following plot shows the finish date for the example model ‘Parallel correlation
example’:

The plot shows that this project has about a 20% probability of finishing before 26 Oct 2018. By hovering over the plot with your mouse you can see the probability more precisely for any specific date, for example:

which shows that there is a 64% probability that the task will finish before 10 Nov 2018.

## Cumulative descending plot

The
cumulative descending plot shows the duration (or date) on the horizontal
axis and the probability of *falling
above* that duration (or date) on the vertical axis. For example:

## Pareto plot

The ribbon shown with the Pareto plot is as follows:

The Pareto plot is a combination of the Histogram and cumulative ascending plots. The horizontal axis shows the duration (or date). The left vertical axis shows the scaling for the histogram plot, and the right vertical axis shows the scaling for the cumulative ascending plot. Hovering over the plot with the mouse will allow you to read off both scales:

## Tornado plot

A Tornado plot illustrates the sensitivity of the output of a selected task to the other variables in the model. Select a task, a property (start, finish, duration, cost) and click the Tornado icon.

The
length of the bar (in days) represents the difference, on average, in
the property of the selected parent task between when each influencing
uncertain component in the model (either a child, a risk event, a task
that may or may not occur, or a risk factor) is at a very low or a very
high value. Thus, the longer the bar, the greater the influence of the
model component. *Tamara* automatically
filters out and plots the most influential among them, according to the
number of bars selected in the ribbon control and the number of levels
that *Tamara* is instructed
to drill down:

The
Tasks, Risk Events, Risk existence and (Productivity) Risk factors icons
toggle on and off when clicked. Clicking Tasks *on*
and Risk Events *off*, for example,
will display the sensitivity of the parent task to child task durations
alone:

Conversely,
clicking Tasks *off* and Risk
Factors *on* will display the
sensitivity of the parent task to risk events alone:

Clicking everything on will display the sensitivity of the parent task to child task durations in blue and risk events and factors in red:

## Periodic cashflow

The periodic cashflow plot allows you to see the amount of money that is projected to be spent during each period of the project for any selected task or summary level. . To view, select Trend from the view options, and Periodic from the Trend options. The period can be switched between different periodic lengths (days, weeks, etc) in the Cost Summation Period part of the ribbon:

## Cumulative cashflow

The cumulative cashflow plot allows you to see the total amount of money that is projected to be spent up to and including specific dates for any selected task or summary level. . To view, select Trend from the view options, and Cumulative from the Trend options. The time between each measurement date can be altered (days, weeks, etc) in the Cost Summation Period part of the ribbon:

## Finish date - total cost scatter plot

It is also possible to plot a scatter plot of the finish date and related cost - again, for any selected task or summary level. In the following examples, the plots show the cost and time for the Electrical part of the project. There are two options:

### Option 1: Scatter plot with a trend line

This plots the total cost and finish dates together, and draws a line showing the mean cost accumulated during each period:

To view, select Trend from the view options, Scatter from the Trend options, and ensure that the Show Trend Line option is ticked in the Scatter Options section of the ribbon. The period can be switched between different periodic lengths (days, weeks, etc) in the Cost Summation Period part of the ribbon.

### Option 2: Scatter plot without a trend line

This plots the total cost and finish dates together:

To view, select Trend from the view options, Scatter from the Trend options, and ensure that the Show Trend Line option is unticked in the Scatter Options section of the ribbon.

## Stochastic Gantt chart

You can also see a Gantt chart with information showing the uncertainty about when each task will start and finish. Click the Stochastic Gantt tab. On the left is a collapsible list of the tasks, by default aggregated to level 1. On the right box plots show the range of dates each task will start and finish. Hovering over the task with the mouse makes a pop-up appear with detailed information. The following plots shows a stochastic Gantt chart with finish dates only, for a selected number of tasks:

The Outer and Inner Envelope parameters allow you to specify the probability ranges that are shown in the box plot. For example, by selecting 5% for the outer envelope, the box plot arms will extend out to the P05 and P95 values. Selecting 25% for the inner envelope, the red box (inner envelope) will cover the P25 to 75 range. A tooltip pops up when hovering over each plot, showing which percentiles are plotted and their values (see above).

####
**ModelRisk**

Monte Carlo simulation in Excel. Learn more

####
**Tamara**

Adding risk and uncertainty to your project schedule. Learn more

####
**Navigation**

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- Modeling expert opinion
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- Classical statistics
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- Bayesian inference
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- Bootstrap

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- Miscellaneous
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- About array functions in Excel

- Excel and ModelRisk model design and validation techniques

- Monte Carlo simulation
- RISK ANALYSIS SOFTWARE
- Risk analysis software from Vose Software
- ModelRisk - risk modeling in Excel
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- Aggregate DePril
- Aggregate Discrete
- Expert

- ModelRisk introduction
- Building and running a simple example model
- Distributions in ModelRisk
- List of all ModelRisk functions
- Custom applications and macros

- ModelRisk functions explained
- Tamara - project risk analysis
- Introduction to Tamara project risk analysis software
- Launching Tamara
- Importing a schedule
- Assigning uncertainty to the amount of work in the project
- Assigning uncertainty to productivity levels in the project
- Adding risk events to the project schedule
- Adding cost uncertainty to the project schedule
- Saving the Tamara model
- Running a Monte Carlo simulation in Tamara
- Reviewing the simulation results in Tamara
- Using Tamara results for cost and financial risk analysis
- Creating, updating and distributing a Tamara report
- Tips for creating a schedule model suitable for Monte Carlo simulation
- Random number generator and sampling algorithms used in Tamara
- Probability distributions used in Tamara
- Correlation with project schedule risk analysis

- Pelican - enterprise risk management
- ModelRisk Cloud system
- ModelRisk Cloud introduction
- Getting your software ready
- Starting ModelRisk Cloud
- Uploading a risk analysis model
- Creating a new scenario for the risk analysis model
- Running a Monte Carlo simulation of the model
- Uploading a SID (Simulation Imported Data file)
- Building a risk analysis model that uses SIDs
- Viewing the Monte Carlo results from a simulation run
- Administrator's use of ModelRisk Cloud
- Preparing a risk analysis model for upload to ModelRisk Cloud

- ModelRisk Result Viewer