I attended several talks about R at the Joint Statistics meetings and noted some interesting packages and other resources during these talks. I lost track of that list until recently, but they are still relevant, so here they are. Continue reading
This is a series of videos and homework exercises that you can work on at your own pace. I have only viewed the outline for this, but anything from DataCamp comes highly recommended. Continue reading
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
This paper talks about how to get students to think about large databases in an introductory class that normally uses “toy” problems with a few dozen rows of data. Continue reading
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
The Teaching of Statistics in the Health Sciences (TSHS) section of the American Statistical Association has put together a set of resources for teachers including several very interesting datasets. some of the resources are open to anyone, but others require a registration. Continue reading
As a community, we statisticians have known for a long time that we do not teach that introductory level class in Statistics as well as we should. This guideline list the things and ways we SHOULD teach as well as things that we might think about leaving out. Continue reading
This is a very clear, but also very detailed explanation of the for, while, and repeat loops along with the concept of vectorization. A great resource for beginners. Continue reading
I’m so busy these days that it is silly to take on anything new, but I found an opportunity for a small research grant that I might want to submit a proposal for. Continue reading
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