One of the themes of this blog is to make statistics relevant and exciting to students by helping them understand the data that’s right under their noses. Or inside their ears. The iTunes library is a great place to start.
For awhile, iTunes made it easy to get your data onto your hard drive in a convenient, analysis-ready form. Then they made it hard. Then (10.7) they made it easy again.
In an effort to integrate more hands on data analysis in my introductory statistics class, I’ve been assigning students a project early on in the class where they answer a research question of interest to them using a hypothesis test and/or confidence interval. One goal of this project is getting the students to decide which methods to use in which situations, and how to properly apply them. But there’s more to it – students define their own research question and find an appropriate dataset to answer that question with.
With fewer than two weeks left till the US presidential elections, motivating class discussion with data related to the candidates, elections, or politics in general is quite easy. So for yesterday’s lab we used data released by The Federal Election Commission on contributions made to 2012 presidential campaigns. I came across the data last week, via a post on The Guardian Datablog. The post has a nice interactive feature for analyzing data from all contributions.
I was creating a dataset this last week in which I had to partition the observed responses to show how the ANOVA model partitions the variability. I had the observed _Y _(in this case prices for 113 bottles of wine), and a categorical predictor X (the region of France that each bottle of wine came from). I was going to add three columns to this data, the first showing the marginal mean, the second showing the effect, and the third showing the residual.
Simply Statistics lists some data analysis projects. Skewing towards the intermediate rather than novice student. But still useful in many ways. And—some FitBit ideas!
http://simplystatistics.org/post/32881133740/statistics-project-ideas-for-students-part-2
A little bit ago [July 19, 2012 — so I’m a little behind], the L.A. Times ran an article about whether TV hosts are pulling their own weight, salary wise. (What is the real value of TV stars and personalities?) I took their data table and put it in a CSV format, and added a column called “epynomious”, which indicates whether the show is named after the host. (This apparently doesn’t explain the salary variation.
I attended useR! 2012 this past summer and one of the highlights of the conference was a presentation by Yihui Xie and JJ Allaire on knitr. As an often frustrated user of Sweave, I was very impressed with how they streamlined the process of integrating R with LaTeX and other document types, and I was excited to take advantage of the tools. It also occurred to me that these tools, especially the simpler markdown language, could be useful to the students in my introductory statistics course.
