**Purpose: **This document gives examples of some of the different types of histograms, dot plots and box plots that can be made using the Tuva Tools.

**How to Use: **Skim the examples to gain inspiration for different Plot States (graphical displays) you can create for the lessons you author or that you can have students make in the course of a lesson.

**Example One: Dot Plot with Mean Dividers and Colored by Type**

The dividers, combined with percentages, can segment a dot plot into sections. The example below divides the data into segments of 25%-50%-25%. This approach allows students to grasp the distribution's spread, paving the way for understanding advanced graphs such as the box plot.

**Example Two: Parallel Dot Plots with Median and Interquartile Range and Colored by Group**

You can create parallel dot plots to compare two groups by splitting the data by a categorical attribute. You can then display statistics such as the median and the interquartile range to compare the center and spread of the two distributions.

**Example One: Frequency Histogram**

Histograms group numerical data into segments or "bins". In the example below, the first bin ranges from 0 to 5, and the second from 5 to 10. The height of each bar indicates the number or frequency of dinosaurs within each bin. Histograms are best for visualizing large datasets.

**Example Two: Parallel Relative Proportion Histogram**

This graph presents a parallel histogram split by the categorical attribute "Hip Type." The height of the bars indicate the relative proportion for each bin. Additionally, a color-coded legend represents different geological periods, adding another layer of information. Parallel histograms are very useful for making comparisons between two groups.

**Example Five: Parallel Box and Dot Plots**

Box plots clearly show the center, spread, and shape of distributions and allow for easy comparison between different distributions. However, they also hide individual data points. In Tuva, box plots can be displayed with the underlying dot plot visible, making it easy to relate the number of points in a section of the box plot with how their density is represented.

**Example Six: Parallel Box Plot with Outliers**

It is also possible to have the program identify outliers in a box plot. When you select **Box>Box Plot with Outliers**, the outliers show up as dots on either side of the box. Dots that are not outliers do not show up. In the example below, the dots are also colored by **Diet.**