1. R and presentations: a basic example of knitr and beamer:  Combine the knitr package with the Latex package beamer for presentation slides, instead of the the Sweave package because it basically is a better Sweave.
  2. Constructing Summary Statistics for Approximate Bayesian Computation: Semi-automatic ABC : a good paper worthy of learning and discussing. Many modern statistical applications involve inference for complex stochastic models, where it is easy to simulate from the models, but impossible to calculate likelihoods. Approximate Bayesian computation (ABC) is a method of inference for such models. It replaces calculation of the likelihood by a step which involves simulating artificial data for different parameter values, and comparing summary statistics of the simulated data to summary statistics of the observed data.
  3. Elegant & fast data manipulation with data.table : Extension of data.frame for fast indexing, fast ordered joins, fast assignment, fast grouping and list columns.
  4. Ordinal Measures of Association : These statistics I have met for twice so far. The recent one is in this paper written by Han Liu etc.
  5. Table design : Almost every research paper and the­sis in sta­tis­tics con­tains at least some tables, yet stu­dents are rarely taught how to make good tables. While the prin­ci­ples of good graph­ics are slowly becom­ing part of a sta­tis­ti­cal edu­ca­tion (although not an econo­met­rics edu­ca­tion!), the prin­ci­ples of good tables are often ignored.
  6. Dirichlet distribution