# Tutorial: Open a model to browse

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This Tutorial page shows you how to open and explore an example Analytica model: The **Rent vs. Buy model** compares the total cost of renting a house to the cost of buying one.

You can start by viewing this video, or jump straight into starting up the model in Analytica.

**Video:** Tutorial: Open a model to browse (7 minutes)

## Open the Rent vs. Buy model

To begin, follow these steps.

- You start Analytica like any Windows application: For example, click the
**Start**button on the Windows taskbar. Click**All Programs**→**Analytica 4.6**→**Analytica 4.6**. - After Analytica starts, select
**File**→**Open**from the menu. -

- Open the Rent vs. Buy model.

Analytica reads in the Rent vs. Buy model.

## The Diagram window

When you open a model, Analytica first displays a top-level Diagram window. The *Rent vs. Buy* model diagram shows several input variables that affect the trade-offs between renting and buying, **Normal** buttons, a **Calc** button, and a node labeled Model.

This top-level diagram is an end-user interface to the model itself, which is contained in the Model node. In this chapter, you use only the interface in this top level diagram; in the following chapters you will explore the model in more depth.

Across the top of the screen is a horizontal palette of buttons. This is called the * tools palette*.

When you first open the *Rent vs. Buy* model, the **browse tool** is highlighted on the palette. With the browse tool selected, the cursor looks like a hand when it is over the diagram. The browse tool allows you to calculate the model, change input values, and examine — but not change — the structure of the model. In this chapter, you only use the browse tool.

## Access Help Resources

At any time, you can press the *F1* key on the keyboard or use the **Help** menu to access Analytica’s help resources online. This menu includes links to this [[Analytica Tutorial|Tutorial], the User Guide and much more tips and reference material on this Analytica Wiki.

## Compute output values

In the *Rent vs. Buy* model, the output value of interest is at the bottom, *Present value of buying and renting*.

The output value displays in a Result window. This **Result** window shows a graph of two * probability density* curves, one for buying and one for renting. In a probability density graph, the units of the vertical scale are chosen so that the total area under each curve is 1 (100%). 25μ corresponds to 25 x 10-6 or 0.000025.

Since the graph is of probability densities, both buying and renting have probabilistic, or uncertain, inputs. The probability density graph for each appear to be bell-shaped curves (normal distribution), although they appear a bit “noisy.”

The graphs show that the cost of renting, given the model’s inputs, are between about $105,000 and $155,000 (the negative numbers mean cost — cash flowing out), while the cost of buying is between $115,000 and a gain of $75,000.

**Note**: Your results can vary slightly, since the model is generating random inputs based on a normal distribution for the uncertainty of the rate of inflation and for the appreciation rate.

Click the model Diagram window to bring it to the front. Notice that the button next to *Costs of buying and renting* has changed to **Result**. The **Result** button indicates that the value has been computed; clicking the **Result** button re-displays the computed values.

## Change input values and recompute results

Now you will change some input values to the model and recompute the rent vs. buy comparison. You will change the values of *Time horizon*, *Monthly rent*, and *Buying price*.

As soon as you change an input, the **Result** button changes to a **Calc** button, indicating that *Present value of buying and renting* needs to be recomputed.

Now you are ready to recompute to see the new results.

The graphs show that the cost of renting, given these changed inputs, is between $90,000 and $120,000, while the cost of buying is between $135,000 and a gain of $70,000.

## Examine and change an uncertain input

When an input is defined as a probability distribution, a button with the name of the distribution appears next to the input’s name. Clicking this button opens the Object Finder window, in which you can see details and change the distribution’s parameters or type of distribution.

*Rate of inflation*’s button says **Normal**, indicating that it is defined as a normal distribution.

The Object Finder window appears. It shows that *Rate of inflation* is defined as a normal distribution with a * mean* of 3.5 and a

*of 1.3.*

**standard deviation**You will now modify the probability distribution that defines *Rate of inflation*. Rather than using the normal distribution, you will use the uniform distribution, and assume that inflation has an equal probability of being anywhere between 3% and 4% per year.

The graphs show that the uncertainty in the cost of renting has narrowed to between about $105,000 and $109,000, while the uncertainty in the cost of buying has flattened to between about $125,000 and a gain of $10,000.

## Display alternative uncertainty views

Analytica offers a variety of views to display uncertain values, including selected statistics, probability bands, the probability density function, the cumulative probability distribution function, measures of central tendency, and the table of random numbers from which the uncertain distribution is estimated.

You will now examine several of these views.

In the upper-left corner of the Result window is the Uncertainty View popup menu.

The miniature probability distribution indicates that * Probability Density* is selected.

The Result window now shows two cumulative probability curves. Along the vertical axis, these curves give the probability that each cost is less than a given value along the horizontal axis.

There appears to be about a 50% probability that the cost to buy is below $70,000, while the cost to rent has a 50% probability of being below about $110,000.

Sometimes you might want to see an uncertain value expressed as a single number — a measure of central tendency. Analytica computes the mid value (sometimes called the * deterministic value*) by fixing all input probability distributions at their median (50% probability) values. The mid value is the only uncertainty view available for nonprobabilistic results.

The Result window now displays bar graphs for the two mid values.

Under the Uncertainty View popup menu are two buttons, and . The is highlighted, indicating that the **Result** window is displaying a graph view. The **Result** window can also display numeric values in a spreadsheet-like table view.

Analytica also provides the mean (or average) value.

You can also view a set of statistics, including both the median and mean, the ranges (minimum and maximum), and the standard deviation.

The Result window now displays the minimum, median^{[1]}, mean, maximum, and standard deviation for *Costs of buying and renting*.

The statistics might not be exact, because they are estimated from a sample of values from the distribution.

Finally, you see the sample values.

The table above lists the 100 sample values that Analytica randomly generated from the probability distribution to estimate the statistics.

A sample size of 100 is adequate for most applications; however, if you need more precise estimates, you can increase the sample size. See Uncertainty Setup dialog in the Analytica User Guide.

## Save your model

If you want to save changes to your model, you can do so at this point. (For instructions on quitting without saving, see the next section.

If you wish to save your model as a different file, so that you do not change the original model, select **Save As** from the File menu.

## Quit Analytica

When you have finished using a model, you might want to quit Analytica.

## Summary

You have now opened an Analytica model, calculated and viewed the results, changes input values and probability distributions, and displayed the uncertain results in several ways. These are the basic techniques for using any quantitative model.

After you create your own models, you might want to give them a top-level input and output diagram like the one used in this chapter. For information about customizing a model for end users, see Creating Interfaces for End Users in the Analytica User Guide.

The next Tutorial page, shows how to navigate the details of the Rent vs. Buy model, exploring its structure and contents.

## Notes

- ↑ Note that the median value is slightly different from the mid value. The mid value is composed of non- probabilistic results generated by using the median value for each input. The median value is calculated using probabilistic inputs and taking the median of the resulting distribution.

## See Also

- Play the Rent vs. Buy model in Analytica Cloud Player
- Using the Rent vs. Buy Model (an explanatory video on YouTube)
- Tutorial videos
- To open or exit a model
- Create and save a model
- Tutorial: Create a model
- Example Models
- Example Models and Libraries
- Diagram window
- Help menu and documentation
- User input nodes and user output nodes
- Expressing Uncertainty
- Uncertainty Setup dialog
- Uncertainty view of a result

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