I just noticed that visual.ly has been running a health data visualization challenge in recent weeks. You have until Sunday, July 22nd, to submit visualizations of data of your choice from HealthData.gov. Both individual and group entries are invited. The prizes for first, second, and third place are pretty sweet, including books, technology, and conference travel.

Let me know if you submit an entry!

As promised here are my solutions to Midterm 2.

And here are clicker questions from Chapters 5 and 6, concerning inferences for proportions and small-sample inferences. Check the last page of the PDF for answers.

Check back here soon for a study guide for the final exam, as well as solutions for the second midterm. Let me know if you have any questions about the final or if there are other materials I can provide that would be helpful.

Here are the clicker questions from Chapter 7, on linear regression. Check the last page of the PDF for answers.

I wanted to share a few ideas for creating infographics with you as you start work on your application projects.

• Option 1 – Use visual.ly, an online tool for creating infographics. I haven’t used it, but I’ve heard great things about it, and I’d love to learn how to use it. I think it’s basically free.
• Option 2 – Use R. I’m pretty comfortable troubleshooting in R if you need help. See below for some resources on using R to create data visualizations. You can export your R plots as PNG or PDF files, then insert them into a PowerPoint or Prezi you use to design the infographic as a whole.
• Option 3 – Use Excel. I’m pretty comfortable troubleshooting in Excel, too. You would need to export these plots into PowerPoint or Prezi, just like with R.
• Option 4 – Use some other program, like Adobe Illustrator or the free, open-source alternative to Illustrator, Inkscape. I don’t know these tools, however, so I probably won’t be able to help you if you get stuck. See this list of tools from Steven Anderson and these ideas for creating infographics from Chris Clark for other possibilities.

Whatever tool you use, be sure you can output an infographic that I can embed one way or another here on the blog. Let me know if you have questions about output options.

Help with R

Flowing Data has some useful tutorials for creating particular data visualizations in R:

• How to Make Bubble Charts
• How to Make a Heatmap

The heatmap tutorial includes a section on color selection. R has a few built-in color palettes, including cm (cyan-magenta) and heat (warm colors), both seen in the tutorial. Other palettes include rainbow, terrain, and topo. You can type things like “?rainbow” in R to find out the parameters for these palettes.

See the Quick-R tutorials on basic graphs and advanced graphs for more R commands useful for data visualization. I used the Flowing Data and Quick-R tutorials, along with R’s help files and a little Internet searching, to create the visualizations back on Problem Set 1.

Here’s a copy of the draft infographic grading rubric I handed out in class yesterday. And here are the two infographic I asked you to grade using the rubric:

• The Automated Workplace: Robots on the Rise
• Shoplifting Around the World

If you didn’t get a chance to evaluate both infographics, please do so before class on Wednesday. Thanks!

Here’s a link to the Google doc we’ll use in class today:

• Infographic Rubric Ideas

And here are the clicker questions for Chapter 4. Answers to the questions, along with some explanations of the more ambiguous questions, are on the final page of the PDF.

Please note: The answer key has an incorrect answer listed for question 11. The correct answer to question 11 is D.

Here are the clicker questions for Chapter 3. Answers to the questions are on the final page of the PDF.

Here’s the Prezi I used during class today to introduce the topic of linear regression. You can step through the Prezi by clicking the forward button, or you can use your mouse to pan and zoom freely throughout the canvas.