Simpocalypse for High School: Statistics

In this project, you'll learn how to use statistical techniques, like measures of central tendency, plots, and regression, to help you interpret the data you get out of a Simpocalypse model. These tools help you reason about large datasets as a whole, and they can also help make predictions about future data based on past data.

The Standards

This project is designed to meet most of the Core Math Standards for high school statistics. (The full list is too long to include here.) It also addresses Michigan Science Standard HS-ETS1-4 and ISTE Students standards 1c, 3a, 3c, 3d, 4a, 4b, 4c, 4d, 5a, 5b, 5c, 5d, 6a, 6c, 6d, 7b, and 7c. For more information, you can read our standards summary document, the Core Standards website, Michigan's standards document, and the ISTE's standards page.

The Rubric

You can see the rubric that your teacher will use to grade your project here.

The Project

You'll have a lot to do over the next six weeks or so. We'll be learning about the biology of infectious diseases, practicing with Simpocalypse itself, actually creating a disease model and generating data from it, and then using the data to apply all the cool statistical techniques we're really here to learn.

Important Links

• The Simpocalypse website, where you can download Simpocalypse itself, and get help with using it.
• The CODAP website provides access to the excellent CODAP data science application, which you'll find very helpful for some kinds of statistical analysis, especially 2D scatter charts, box plots, and linear regression.
• You might want to use Simpocalypse's database export feature to analyze your data. If you don't know any computer coding, or you don't know how to code with SQL in particular, SQLiteBrowser is the easiest way to open Simpocalypse database files.
• If you're a teacher, you can get more information about the project from our summary presentation and sign your class up with our signup form.

Step By Step

• First, we'll need to review some basics about the biology of infectious diseases, so you have the basic background information you need to understand the biological aspects of the project. The STEM Explorer team is creating some lesson plans to help you with this.
• Next, you'll learn how to use the Simpocalypse application. The Simpocalypse website contains, besides the download links for Simpocalypse itself, the Simpocalypse manual, some suggested activities, and some tutorials to help you get started. Depending on your situation, the STEM Explorer team might come to your school to help, or give lectures over videoconference.
• After this it'll be time to go out and research historical epidemics and pandemics, paying particular attention to finding statistical data about them so you can recreate the epidemic later, in Simpocalypse. The Simpocalypse website has some information to get you started, but you'll need to do some digging on your own, too. At the end of this process your team should pick a historical disease to work with for the rest of the project
• Once you know which disease you'll focus on, it's time to learn some statistics! This part will be mostly up to your teacher, but the important thing is that you learn about the tools, like plots and linear regression, that you'll be using later to analyze your Simpocalypse data.
• Now, you know what you need to start playing with Simpocalypse! You'll need to recreate your historical disease as accurately as possible, within the limitations of the historical records that you have access to. Once your Simpocalypse model is working pretty well, you can start collecting data from it.
• Next, you'll take your exported data and try to find interesting things in it. This part of the project is perhaps the most important, but it's also pretty open-ended. You have the statistical tools you'll need to do things like measure the effects that changes to the parameters have on the results, visualize the way different parameters are related to each other, and approximate certain results with relatively simple mathematical functions (which you might use, for example, to predict how future data in the simulation will look based on the first part). During this process you'll probably end up tweaking your model, so you can measure how the results change.
• When you're all done, you'll write a report about your findings, describing your simulation's results using statistical language. Depending on your teacher's preferences, you might just submit a written report, or you may give a presentation about your investigation.