Tag Archives: Teaching resources

Recommended: beanumber repository

This is the github repository of Ben Baumer. He is one of the co-authors of “Modern Data Science with R” and the data and code from that book is available here. He also provides code and data for OpenWAR, an open source method for calculating a baseball statistic, Wins Above Replacement. Finally, there is an R library for extracting, transforming, and loading “medium” sized datasets into SQL. Medium here means multi-gigabyte sized files. Related to this are a couple of “medium” sized data sets from the Internet Movie Database and from the NYC CitiBike dataset. Continue reading

Recommended: Announcing a new monthly feature: What’s going on in this graph

Through the effort of a team of statisticians with the American Statistical Association, the New York Times is producing a new resource for educators called “What’s Going On in This Graph?”. This is similar to another New York Times effort called “What’s Going On in This Picture?”

Every month the New York Times will publish a graph stripped of some key information and ask three questions: What do you notice? What do you wonder? and What do you think is going on in this graph?

The content will be suitable for middle school and high school students, but I suspect that even college students will find the exercise interesting.

The first graph will appear on September 19 and on the second Tuesday of every month afterwards. Continue reading

Recommended: Diverse Perspectives on a Flipped Biostatistics Classroom

This article is a synthesis of a panel discussion at the 2014 Joint Statistical Meetings on the flipped classroom. The article discusses it solely from the perspective of Biostatistics classes, though they offer some references for the flipped classroom in a more general setting. A flipped classroom is a course where the traditional didactic lectures are recorded and watched at home and the homework that would normally be done at home is done instead in the classroom. This homework in a Biostatistics class often takes the form of active learning in small groups, such as critiquing published research studies or conducting analyses on real world data sets. The key component, according to the authors, is the in class interactions during these assignments. Students learn from each other as they work in groups.

Now you could do active learning in a traditional course format. What a flipped classroom does is increases the emphasis and the amount of time spent in active learning.

The common theme of the paper is that the flipped classroom has been successfully applied in a variety of settings. It is not a “one size fits all” approach, but rather can be adapted to the needs of the particular class. Some students may not like the flipped classroom format, and you shouldn’t underestimate the amount of time needed to prepare the videotaped lectures (one rule of thumb is ten hours of work for every hour of video). Still the student reactions and the instructors perceptions of the flipped classroom are generally positive. Continue reading

PMean: Bad examples of data analysis are bad examples to use in teaching

I’m on various email discussion groups and every once in a while someone sends out a request that sounds something like this.

I’m teaching a class (or running a journal club or giving a seminar) on research design (or evidence based medicine or statistics) and I’d like to find an example of a research study that use bad statistical analysis.

And there’s always a flood of responses back. But if I were less busy, I’d jump into the conversation and say “Stop! Don’t do it!” Here’s why. Continue reading