Links Links Links

A new bunch of links to the resources regarding statistics etc. that seem to me helpful:

Introduction to Statistics

This is an archive of an introductory statistics course at Coursera Statistics: Making Sense of Data by Alison Gibbs, Jeffrey Rosenthal (University of Toronto).

The authors of the course kindly provided a list of recommended literature. I don’t think it would be a crime to reproduce it here. So, they recommended three ‘traditional books’:

  • Introduction to the Practice of Statistics, by David S. Moore and George P. McCabe. (The book is currently in its fifth edition, but any edition will do.)
  • Stats: Data and Models, Canadian edition, by Richard D. De Veaux, Paul F. Velleman, David E. Bock, Augustin M. Vukov, and Augustine C.M. Wong. (The original version of the book, by the first three authors only, is also recommended.)
  • Statistics, by David Freedman, Robert Pisani, and Roger Purves.

And three online resources:

  • OpenIntro Statistics, by David M. Diez, Christopher D. Barr, and Mine Cetinkaya-Rundel. The cool thing about this one is that it’s not just a book, it’s a whole learning tool including labs and some instructions on using R.
  • Online Statistics Education, by David M. Lane, David Scott, Mikki Hebi, Rudy Guerra, Dan Osherson, and Heidi Zimmer
  • HyperStat Online, by David M. Lane
  • StatPrimer, by B. Burt Gerstman

R

Statistics and Python

And last, a couple of books kindly recommended by a great person at P2PU. These connect statistics to programming in Python:

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Back to learning. Statistics, R

OK, here am I back from my over a month’s time gap, of which there were two weeks of holydays and the rest was a huge lump of work, including the tasks for my job as well as some work at Moscow Open Data School. But now I hope I’ll be able to afford to spend some time on just learning.

Unfortunately, I couldn’t finish my Python MOOC, because of that sudden workload again. But I’m totally going to get back to it as soon as I can. Following Zach Sims’ (Codecademy) recommendation, I’m simply trying to gradually do the tasks Codecademy to refresh stuff in my mind and to keep digesting Python.

Right now though I’m focused on the Statistics course that has just begun at Coursera (by the way, those who are interested are welcome to join). I wonder how helpful it’s going to be, but there’s one thing I know for sure: I’ve got to learn how to process data in R. And well, the R course is actually integrated into this one, which is great.

While working on the first assignment, which was actually a very simple drill exercise to memorize some R commands, I faced one problem. The problem was that I couldn’t install and load a package in R (MS Windows 7) because of some troubles with administrator access to some saving functions (although I’m obviously the administrator). Or better to say, it did download the package, but it would refuse to save it in the R directory. As far as I know, some students in the same course also had troubles at this point, but they were different. In my case the solution was very simple. I just manually relocated the necessary package from where it was saved by default to where I needed it (namely, in the R library). And there’s also a way to install packages from a manually downloaded (from CRAN) .zip files through the menu (Packages > Install package(s) from local zip files). Well, at this stage this works perfectly well for me.

And here are some helpful links: