---
title: "Selecting variables to simulate"
slug: "selecting-variables-to-simulate"
updated: 2022-06-28T18:32:16Z
published: 2022-06-28T18:32:16Z
canonical: "userguide.dataclassroom.com/selecting-variables-to-simulate"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://userguide.dataclassroom.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Selecting variables to simulate

From the Simulation Model, you can create a new Simulation, using the **Simulate...** option in the left-hand menu.

You can now choose how to look at these variables:

- **One** variable will be the **Response variable**. This is the main "outcome" or "property" you are looking at in your simulated experiment.
- You can also choose **one or two** other variables as **Predictor variables**. These would typically be those you are investigating to find a relationship with the Response variable.

These are shown on the Simulation screen like this:

![](https://cdn.document360.io/62f8f41e-e041-42c4-b9bc-8ae1eb45d064/Images/Documentation/image-1656402420622.png)

Changing variables after having run the simulationChanging how your simulation is set up (like switching variables) is a major change, and means that any **previous results** are no longer relevant. You will be asked whether you want to **delete all your previous runs** if you change variables in a Simulation.

### Showing variables on the graph

The graph will show your Response variable, either as a **histogram** (for numeric variables) or as bars (**frequency chart**) for categorical variables.

If you have a **categorical predictor variable**, this can be used to group the results by the variable's values, by checking the **Group by** checkbox.

![](https://cdn.document360.io/62f8f41e-e041-42c4-b9bc-8ae1eb45d064/Images/Documentation/image-1656402779958.png)

If you have more than one **predictor variable** you can select which one you want to use for the visualization.

If you **create a dataset** from the samples in one of your runs, these settings will also be used to **set up the graph** in the dataset.