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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