Podcast #6: Data Analysis MOOC Post-mortem

Jeff and I talk about Jeff’s recently completed MOOC on Data Analysis.

Sunday data/statistics link roundup (3/24/2013)

1. My Coursera Data Analysis class is done for now! All the lecture notes are on Github all the videos are on Youtube. They are tagged by week with tags “Week x”.
2. After ENAR the comments on how to have better stats conferences started flowing. Check out Frazee, Xie, and Broman. My favorite cherry picked ideas: conference app (frazee), giving the poster session more focus (frazee), free and announced wifi (broman), more social media (i loved following ENAR on twitter but wish there had been more tweeting) (xie), add some jokes to talks (xie).
3. A related post is this one from Hilary M. on how a talk should entertain, not teach.
4. This is a [ 1. My Coursera Data Analysis class is done for now! All the lecture notes are on Github all the videos are on Youtube. They are tagged by week with tags “Week x”.
5. After ENAR the comments on how to have better stats conferences started flowing. Check out Frazee, Xie, and Broman. My favorite cherry picked ideas: conference app (frazee), giving the poster session more focus (frazee), free and announced wifi (broman), more social media (i loved following ENAR on twitter but wish there had been more tweeting) (xie), add some jokes to talks (xie).
6. A related post is this one from Hilary M. on how a talk should entertain, not teach.
7. This is a](http://blogs.spectator.co.uk/books/2013/03/interview-with-a-writer-jaron-lanier/) I found via AL Daily. My favorite lines? “You run into this attitude, that if ordinary people cannot set their Facebook privacy settings, then they deserve what is coming to them. There is a hacker superiority complex to this.” I think this is certainly something we have a lot of in statistics as well.
8. The CIA wants to collect all the dataz. Call me when cat videos become important for national security, ok guys?
9. Given I just completed my class, the MOOC completion rates graph is pretty appropriate. I think my #’s are right in line with that other people report. I’m still trying to figure out how to know how many people “completed” the class.

Youtube should check its checksums

I am in the process of uploading the video lectures for Data Analysis. I am getting ready to send out the course wrap-up email and I wanted to include the link to the Youtube playlist as well.

Unfortunately, Youtube keeps reporting that a pair of the videos in week 2 are duplicates. This is true despite them being different lengths (12:15 vs. 16:58), having different titles, and having dramatically different content. I [I am in the process of uploading the video lectures for Data Analysis. I am getting ready to send out the course wrap-up email and I wanted to include the link to the Youtube playlist as well.

Unfortunately, Youtube keeps reporting that a pair of the videos in week 2 are duplicates. This is true despite them being different lengths (12:15 vs. 16:58), having different titles, and having dramatically different content. I](http://productforums.google.com/forum/#!topic/youtube/Yc7hHqwtBX0) on the forums:

YouTube uses a checksum to determine duplicates. The chances of having two different files containing different content but have the same checksum would be astronomical.

That isn’t on the official Google documentation page, which is pretty sparse, but is the only description I can find of how Youtube checks for duplicate content. A checksum is a function you apply to the data from a video that (ideally) with high probability will yield different values when different videos are uploaded and the same value when the same video is uploaded. One possible checksum function could be the length of the video. Obviously that won’t work in general because many videos might be 2 minutes exactly.

Regardless, it looks like Youtube can’t distinguish my lecture videos. I’m thinking Vimeo or something else if I can’t get this figured out. Of course, if someone has a suggestion (short of re-exporting the videos from Camtasia) that would allow me to circumvent this problem I’d love to hear it!

Update: I ended up fiddling with the videos and got them to upload. Thanks to the helpful comments!

Call for papers for a special issue of Statistical Analysis and Data Mining

David Madigan sends the following. It looks like a really interesting place to submit papers for both statisticians and data scientists, so submit away!

Statistical Analysis and Data Mining, An American Statistical Association Journal

Call for Papers

Special Issue on Observational Healthcare Data

Guest Editors: Patrick Ryan, J&J and Marc Suchard, UCLA

Due date: July 1, 2013

Data sciences is the rapidly evolving field that integrates

mathematical and statistical knowledge, software engineering and large-scale data management skills, and domain expertise to tackle difficult problems that typically cannot be solved by any one discipline alone.  Some of the most difficult, and arguably most important, problems exist in healthcare.  Knowledge about human biology has exponentially advanced in the past two decades with exciting progress in genetics, biophysics, and pharmacology.  However, substantial opportunities exist to extend the evidence base about human disease, patient health and effects of medical interventions and translate knowledge into actions that can directly impact clinical care.  The emerging availability of 'big data' in healthcare, ranging from prospective research with aggregated genomics and clinical trials to observational data from administrative claims and electronic health records through social media, offer unprecedented opportunities for data scientists to contribute to advancing healthcare through the development, evaluation, and application of novel analytical solutions to explore these data to generate evidence at both the patient and population level.  Statistical and computational challenges abound and

methodological progress will draw on fields such as data mining,

epidemiology, medical informatics, and biostatistics to name but a

few.  This special issue of Statistical Analysis and Data Mining seeks to capture the current state of the art in healthcare data sciences. We welcome contributions that focus on methodology for healthcare data and original research that demonstrates the application of data sciences to problems in public health.

http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1932-1872

Sunday data/statistics link roundup (3/17/13)

1. A post on the Revolutions blog about an analysis of the worldwide email traffic patterns. The corresponding paper is also pretty interesting. The best part is the whole analysis was done in R. 
2. A bill in California that would require faculty approved online classes to be given credit. I think this is potentially game changing if it passes - depending on who has to do the approving. If there is local control within departments it could be huge. On the other hand, as I’ll discuss later this week, there is still some ground to be made up before I think MOOCs are ready for prime time credit in areas outside of the very basics.
3. A pretty amazing blog post about a survival analysis of RuPaul’s drag race. Via Hadley.
4. If you are a statistician hiding under a rock you missed the NY Times messing up P-values.  The statistical blogosphere came out swinging. Gelman, Wasserman, Parker, etc.
5. As a statistician who is pretty fired up about the tech community, I can get lost a bit in the hype as much as the next guy. I thought this article was pretty sobering. I think the way to make sure we keep innovating is having the will to fund long term companies and long term research. Look at how it paid off with Amazon…
6. Broman on interactive graphics is worth a read. I agree that more of our graphics should be interactive, but there is an inherent tension/tradeoff in graphics, similar to the bias variance tradeoff. I’m sure there is a real word for it but it is the flexibility vs. understandability tradeoff. Too much interaction and its hard to see what is going on, not enough and you might as well have made a static graph.