# Documentation

## Create Scatter and List Plots

 Note:   Use only in the MuPAD Notebook Interface. This functionality does not run in MATLAB.

Scatter plots can help you identify the relationship between two data samples. A scatter plot is a simple plot of one variable against another. For two discrete data samples x1, x2, ..., xn and y1, y2, ..., yn, a scatter plot is a collection of points with coordinates [x1, y1], [x2, y2], ..., [xn, yn]. To create a scatter plot in MuPAD®, use the `plot::Scatterplot` function. For example, create the scatter plot for the following data samples `x` and `y`:

```x := [0.25, 0.295, 0.473, 0.476, 0.512, 0.588, 0.629, 0.648, 0.722, 0.844]: y := [0.00102, 0.271, 0.378, 0.478, 0.495, 0.663, 0.68, 0.778, 0.948, 0.975]: plot(plot::Scatterplot(x, y))```

By default, the `plot::Scatterplot` function also displays a regression line. This line shows the linear dependency that best fits the two data samples. To hide the regression line, use the `LinesVisible` option:

`plot(plot::Scatterplot(x, y, LinesVisible = FALSE))`

Another plot that can help you identify the relationship between two discrete data samples is a list plot. List plots are convenient for plotting one data sample with equidistant `x`-values. They are also convenient for plotting combined data samples, such as [[x1, y1], [x2, y2], ..., [xn, yn]]. If you have two separate data samples, you can combine the data of these samples pairwise:

`xy := [[x[i], y[i]] \$ i = 1..10]:`

To create a list plot, use the `plot::Listplot` function:

`plot(plot::Listplot(xy), AxesTitles = ["x", "y"])`

By default, the `plot::Listplot` function connects adjacent points on the plot by straight lines. To hide these connections, use the `LinesVisible` option:

```plot(plot::Listplot(xy), AxesTitles = ["x", "y"], LinesVisible = FALSE)```