This book can be used as a companion to a more pedagogical text on survival analysis. For someone looking for an appropriate R command to use, for fitting certain kind of survival model, this book is apt. This book neither gives the intuition nor the math behind the various models. It appears like an elaborate help manual for all the packages in R, related to event history analysis. I guess one of the reasons for the author writing this book is to highlight his package eha on CRAN.

This is a nice article that talks about students' impediments in learning statistics. The article gives a laundry list of recommendations to improve the state of statistical pedagogy at college-level courses. The basic goals for any instructor should be to impart the following ideas: The idea of variability of data and summary statistics. Normal distributions are useful models though they are seldom perfect fits. The usefulness of sample characteristics (and inference made using these measures) depends critically on how sampling is conducted.

The paper titled, Mindless Statistics, by Gerd Gigerenzer, makes a case for banishing the mindless “null ritual” from statistics. In this blog post, I will summarize the main points of the paper. The author starts off by emphasizing the importance of developing a statistical toolbox. Indeed statistics is a rich subject that can be enjoyed by thinking through a given problem and applying the right kind of tools to get a deeper understanding of the problem.

The paper titled, A Multi-Language Computing Environment for Literate programming and Reproducible research, gives an introduction to org-mode. In order to communicate research work to others, it is often important to mix prose and code in same document. There are many tools out there that do the job. However org-mode is one such tool that is useful for literate programming as well as reproducible-research. Be it a research environment or a pedagogical environment, the need for mixing code and prose is always present.

The paper titled, ”Active Documents with Org-mode”, gives a concise introduction to the way org-mode can be used for reproducible research. In one single document, Linux shell commands, Python code and R code are all used for analyzing base-ball statistics. Org-mode is used to produce one comprehensive documents that details all the various steps in the analysis. The following visual from the paper gives an overview of the org-mode document :